3,647 results on '"Moore, Kevin"'
Search Results
2. Composition Rules for Strong Structural Controllability and Minimum Input Problem in Diffusively-Coupled Networks
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Park, Nam-Jin, Kwon, Seong-Ho, Bae, Yoo-Bin, Kim, Byeong-Yeon, Moore, Kevin L., and Ahn, Hyo-Sung
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Mathematics - General Topology - Abstract
This paper presents new results and reinterpretation of existing conditions for strong structural controllability in a structured network determined by the zero/non-zero patterns of edges. For diffusively-coupled networks with self-loops, we first establish a necessary and sufficient condition for strong structural controllability, based on the concepts of dedicated and sharing nodes. Subsequently, we define several conditions for strong structural controllability across various graph types by decomposing them into disjoint path graphs. We further extend our findings by introducing a composition rule, facilitating the analysis of strong structural controllability in larger networks. This rule allows us to determine the strong structural controllability of connected graphs called pactus graphs (a generalization of the well-known cactus graph) by consideration of the strong structural controllability of its disjoint component graphs. In this process, we introduce the notion of a component input node, which is a state node that functions identically to an external input node. Based on this concept, we present an algorithm with approximate polynomial complexity to determine the minimum number of external input nodes required to maintain strong structural controllability in a diffusively-coupled network with self-loops., Comment: 11 pages, 5 figures. arXiv admin note: substantial text overlap with arXiv:2205.05275
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- 2024
3. Older Adults’ Experiences With Using Wearable Devices: Qualitative Systematic Review and Meta-synthesis
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Moore, Kevin, O'Shea, Emma, Kenny, Lorna, Barton, John, Tedesco, Salvatore, Sica, Marco, Crowe, Colum, Alamäki, Antti, Condell, Joan, Nordström, Anna, and Timmons, Suzanne
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Information technology ,T58.5-58.64 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundOlder adults may use wearable devices for various reasons, ranging from monitoring clinically relevant health metrics or detecting falls to monitoring physical activity. Little is known about how this population engages with wearable devices, and no qualitative synthesis exists to describe their shared experiences with long-term use. ObjectiveThis study aims to synthesize qualitative studies of user experience after a multi-day trial with a wearable device to understand user experience and the factors that contribute to the acceptance and use of wearable devices. MethodsWe conducted a systematic search in CINAHL, APA PsycINFO, PubMed, and Embase (2015-2020; English) with fixed search terms relating to older adults and wearable devices. A meta-synthesis methodology was used. We extracted themes from primary studies, identified key concepts, and applied reciprocal and refutational translation techniques; findings were synthesized into third-order interpretations, and finally, a “line-of-argument” was developed. Our overall goal was theory development, higher-level abstraction, and generalizability for making this group of qualitative findings more accessible. ResultsIn total, we reviewed 20 papers; 2 evaluated fall detection devices, 1 tested an ankle-worn step counter, and the remaining 17 tested activity trackers. The duration of wearing ranged from 3 days to 24 months. The views of 349 participants (age: range 51-94 years) were synthesized. Four key concepts were identified and outlined: motivation for device use, user characteristics (openness to engage and functional ability), integration into daily life, and device features. Motivation for device use is intrinsic and extrinsic, encompassing many aspects of the user experience, and appears to be as, if not more, important than the actual device features. To overcome usability barriers, an older adult must be motivated by the useful purpose of the device. A device that serves its intended purpose adds value to the user’s life. The user’s needs and the support structure around the device—aspects that are often overlooked—seem to play a crucial role in long-term adoption. Our “line-of-argument” model describes how motivation, ease of use, and device purpose determine whether a device is perceived to add value to the user’s life, which subsequently predicts whether the device will be integrated into the user’s life. ConclusionsThe added value of a wearable device is the resulting balance of motivators (or lack thereof), device features (and their accuracy), ease of use, device purpose, and user experience. The added value contributes to the successful integration of the device into the daily life of the user. Useful device features alone do not lead to continued use. A support structure should be placed around the user to foster motivation, encourage peer engagement, and adapt to the user’s preferences.
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- 2021
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4. Friday, June 23, 202310:00 AM - 11:00 AMPP01 Presentation Time: 10:00 AM Automating Brachytherapy Treatment Planning for Cervical Cancer Using Neural Network Dose Predictions
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Meyers, Sandra, Moore, Lance C, Kallis, Karoline, Vasconcelos, Nuno, Kisling, Kelly, Rash, Dominique, Yashar, Catheryn M, Mayadev, Jyoti, and Moore, Kevin L
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Biomedical and Clinical Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Clinical Research ,Cancer ,Bioengineering ,Cervical Cancer ,Oncology & Carcinogenesis ,Clinical sciences - Published
- 2023
5. Topological Clusters in Multi-Agent Networks: Analysis and Algorithm
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Ma, Jeong-Min, Lee, Hyung-Gon, Moore, Kevin L., Ahn, Hyo-Sung, and Oh, Kwang-Kyo
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Electrical Engineering and Systems Science - Systems and Control - Abstract
We study clustering properties of networks of single integrator nodes over a directed graph, in which the nodes converge to steady-state values. These values define clustering groups of nodes, which depend on interaction topology, edge weights, and initial values. Focusing on the interaction topology of the network, we introduce the notion of topological clusters, which are sets of nodes that converge to an identical value due to the topological characteristics of the network, independent of the value of the edge weights. We then investigate properties of topological clusters and present a necessary and sufficient condition for a set of nodes to form a topological cluster. We also provide an algorithm for finding topological clusters. Examples show the validity of the analysis and algorithm.
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- 2023
6. Sport History, Public History, and Popular Culture: A Growing Engagement
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Moore, Kevin
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- 2013
7. Fiasco: Formalism, Communication, and Aesthetic Education
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Moore, Kevin Z.
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- 2013
8. Parting at the Windmills: Malamud's The Fixer as Historical Metafiction
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Moore, Kevin C.
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- 2013
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9. Operationalizing Figurative and Operative Framings of Thought
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Moore, Kevin C., Stevens, Irma E., Tasova, Halil I., Liang, Biyao, Cai, Jinfa, Series Editor, Middleton, James A., Series Editor, Dawkins, Paul Christian, editor, Hackenberg, Amy J., editor, and Norton, Anderson, editor
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- 2024
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10. The Canadian National Retirement Risk Index: Employing Statistics Canada’s LifePaths to Measure the Financial Security of Future Canadian Seniors
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MacDonald, Bonnie-Jeanne, Moore, Kevin D., Chen, He, and Brown, Robert L.
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- 2011
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11. Forecasting per-patient dosimetric benefit from daily online adaptive radiotherapy for cervical cancer
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Ghimire, Rupesh, Moore, Kevin L., Branco, Daniela, Rash, Dominique L., Mayadev, Jyoti, and Ray, Xenia
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Physics - Medical Physics - Abstract
Adaptive Radiotherapy (ART) is an emerging technique for treating cancer patients which facilitates higher delivery accuracy and has the potential to reduce toxicity. However, ART is also resource-intensive, requiring extra human and machine time compared to standard treatment methods. In this analysis, we sought to predict the subset of node-negative cervical cancer patients who benefit the most from ART. CT images, initial plan data, and on-treatment Cone-Beam CT (CBCT) images for 20 retrospective cervical cancer patients were used to simulate doses from daily non-adaptive and adaptive techniques. We evaluated the correlation (R$^2$) between dose and volume metrics from initial treatment plans and the dosimetric benefits to the Bowel V$_{40Gy}$, Bowel V$_{45Gy}$, Bladder D$_{mean}$, and Rectum D$_{mean}$ from adaptive radiotherapy using reduced 3mm or 5mm CTV-to-PTV margins. The LASSO technique was used to identify the most predictive metrics for Bowel V$_{40Gy}$. The three highest performing metrics were used to build multivariate models with leave-one-out validation for Bowel V$_{40Gy}$. Patients with higher initial bowel doses were correlated with the largest decreases in Bowel V$_{40Gy}$ from daily adaptation (linear best fit R$^2$=0.77 for a 3mm PTV margin and R$^2$=0.8 for a 5mm PTV margin). Other metrics had intermediate or no correlation. Selected covariates for the multivariate model were differences in the initial Bowel V$_{40Gy}$. and Bladder D$_{mean}$ using standard versus reduced margins and the initial bladder volume. Leave-one-out validation had an R$^2$ of 0.66 between the predicted and true adaptive Bowel V$_{40Gy}$ benefits for both margins. This work could be used to prospectively triage cervical cancer patients, and presents a critical foundation for predicting benefits from daily adaptation that can be extended to other patient cohorts., Comment: 17 pages, 8 figures
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- 2022
12. Painting in Tongues: Faith-Based Languages of Formalist Art
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Moore, Kevin Z
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- 2007
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13. Automated treatment planning framework for brachytherapy of cervical cancer using 3D dose predictions.
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Kallis, Karoline, Moore, Lance, Cortes, Katherina, Mayadev, Jyoti, Moore, Kevin, Brown, Derek, and Meyers, Sandra
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automated planning ,cervical cancer ,dose prediction ,gynecological brachytherapy ,knowledge-based planning ,Female ,Humans ,Uterine Cervical Neoplasms ,Brachytherapy ,Radiotherapy Dosage ,Benchmarking ,Radiotherapy Planning ,Computer-Assisted - Abstract
Objective. To lay the foundation for automated knowledge-based brachytherapy treatment planning using 3D dose estimations, we describe an optimization framework to convert brachytherapy dose distributions directly into dwell times (DTs).Approach. A dose rate kernelḋ(r,θ,φ)was produced by exporting 3D dose for one dwell position from the treatment planning system and normalizing by DT. By translating and rotating this kernel to each dwell position, scaling by DT and summing over all dwell positions, dose was computed (Dcalc). We used a Python-coded COBYLA optimizer to iteratively determine the DTs that minimize the mean squared error betweenDcalcand reference doseDref, computed using voxels withDref80%-120% of prescription. As validation of the optimization, we showed that the optimizer replicates clinical plans whenDref= clinical dose in 40 patients treated with tandem-and-ovoid (T&O) or tandem-and-ring (T&R) and 0-3 needles. Then we demonstrated automated planning in 10 T&O usingDref= dose predicted from a convolutional neural network developed in past work. Validation and automated plans were compared to clinical plans using mean absolute differences (MAD=1N∑n=1Nabsxn-xn) over all voxels (xn= Dose,N= #voxels) and DTs (xn= DT,N= #dwell positions), mean differences (MD) in organD2ccand high-risk CTV D90 over all patients (where positive indicates higher clinical dose), and mean Dice similarity coefficients (DSC) for 100% isodose contours.Main results. Validation plans agreed well with clinical plans (MADdose= 1.1%, MADDT= 4 s or 0.8% of total plan time,D2ccMD = -0.2% to 0.2% and D90 MD = -0.6%, DSC = 0.99). For automated plans, MADdose= 6.5% and MADDT= 10.3 s (2.1%). The slightly higher clinical metrics in automated plans (D2ccMD = -3.8% to 1.3% and D90 MD = -5.1%) were due to higher neural network dose predictions. The overall shape of the automated dose distributions were similar to clinical doses (DSC = 0.91).Significance. Automated planning with 3D dose predictions could provide significant time savings and standardize treatment planning across practitioners, regardless of experience.
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- 2023
14. Safety of Nivolumab Added to Chemoradiation Therapy Platforms for Intermediate and High-Risk Locoregionally Advanced Head and Neck Squamous Cell Carcinoma: RTOG Foundation 3504
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Gillison, Maura L, Ferris, Robert L, Harris, Jonathan, Colevas, A Dimitrios, Mell, Loren K, Kong, Christina, Jordan, Richard C, Moore, Kevin L, Truong, Minh-Tam, Kirsch, Claudia, Chakravarti, Arnab, Blakaj, Dukagjin M, Clump, David A, Ohr, James P, Deeken, John F, Gensheimer, Michael F, Saba, Nabil F, Dorth, Jennifer A, Rosenthal, David I, Leidner, Rom S, Kimple, Randall J, Machtay, Mitchell, Curran, Walter J, Torres-Saavedra, Pedro, and Le, Quynh Thu
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Biomedical and Clinical Sciences ,Clinical Sciences ,Oncology and Carcinogenesis ,Clinical Research ,Digestive Diseases ,Clinical Trials and Supportive Activities ,Rare Diseases ,Immunotherapy ,Radiation Oncology ,Dental/Oral and Craniofacial Disease ,Cancer ,Orphan Drug ,6.1 Pharmaceuticals ,Evaluation of treatments and therapeutic interventions ,Humans ,Squamous Cell Carcinoma of Head and Neck ,Nivolumab ,Cisplatin ,Carcinoma ,Squamous Cell ,Mucositis ,Neoplasm Recurrence ,Local ,Head and Neck Neoplasms ,Fatigue ,Other Physical Sciences ,Oncology & Carcinogenesis ,Oncology and carcinogenesis ,Theoretical and computational chemistry ,Medical and biological physics - Abstract
PurposeProgrammed death-1 immune checkpoint blockade improves survival of patients with recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), but the benefits of addition to (chemo)radiation for newly diagnosed patients with HNSCC remain unknown.Methods and materialsWe evaluated the safety of nivolumab concomitant with 70 Gy intensity modulated radiation therapy and weekly cisplatin (arm 1), every 3-week cisplatin (arm 2), cetuximab (arm 3), or alone for platinum-ineligible patients (arm 4) in newly diagnosed intermediate- or high-risk locoregionally advanced HNSCC. Patients received nivolumab from 2 weeks prior to radiation therapy until 3 months post-radiation therapy. The primary endpoint was dose-limiting toxicity (DLT). If ≤2 of the first 8 evaluable patients experienced a DLT, an arm was considered safe. Secondary endpoints included toxicity and feasibility of adjuvant nivolumab to 1 year, defined as all 7 additional doses received by ≥4 of the first 8 evaluable patients across arms.ResultsOf 39 patients (10 in arms 1, 3, 4 and 9 in arm 2), 72% had T3-4 tumors, 85% had N2-3 nodal disease, and 67% had >10 pack-years of smoking. There were no DLTs in arms 1 and 2, 1 in arm 3 (mucositis), and 2 in arm 4 (lipase elevation and mucositis in 1 and fatigue in another). The most common grade ≥3 nivolumab-related adverse events were lipase increase, mucositis, diarrhea, lymphopenia, hyponatremia, leukopenia, fatigue, and serum amylase increase. Adjuvant nivolumab was feasible as defined in the protocol.ConclusionsConcomitant nivolumab with the 4 tested regimens was safe for patients with intermediate- and high-risk HNSCC, and subsequent adjuvant nivolumab was feasible as defined (NCT02764593).
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- 2023
15. Operationalizing Figurative and Operative Framings of Thought
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Moore, Kevin C., primary, Stevens, Irma E., additional, Tasova, Halil I., additional, and Liang, Biyao, additional
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- 2024
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16. Clinical commissioning of an adaptive radiotherapy platform: Results and recommendations
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Kisling, Kelly, Keiper, Timothy D, Branco, Daniela, Kim, Grace Gwe‐Ya, Moore, Kevin L, and Ray, Xenia
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Medical and Biological Physics ,Biomedical and Clinical Sciences ,Clinical Sciences ,Physical Sciences ,Oncology and Carcinogenesis ,Bioengineering ,Cancer ,Humans ,Radiotherapy Dosage ,Radiotherapy ,Intensity-Modulated ,Cone-Beam Computed Tomography ,Tomography ,X-Ray Computed ,Radiometry ,Radiotherapy Planning ,Computer-Assisted ,Phantoms ,Imaging ,adaptive radiotherapy ,CBCT ,ethos ,on-table adaptation ,quality assurance ,synthetic CT ,workflow ,Other Physical Sciences ,Medical Physiology ,Nuclear Medicine & Medical Imaging ,Medical physiology ,Medical and biological physics - Abstract
Online adaptive radiotherapy platforms present a unique challenge for commissioning as guidance is lacking and specialized adaptive equipment, such as deformable phantoms, are rare. We designed a novel adaptive commissioning process consisting of end-to-end tests using standard clinical resources. These tests were designed to simulate anatomical changes regularly observed at patient treatments. The test results will inform users of the magnitude of uncertainty from on-treatment changes during the adaptive workflow and the limitations of their systems. We implemented these tests for the cone-beam computed tomography (CT)-based Varian Ethos online adaptive platform. Many adaptive platforms perform online dose calculation on a synthetic CT (synCT). To assess the impact of the synCT generation and online dose calculation on dosimetric accuracy, we conducted end-to-end tests using commonly available equipment: a CIRS IMRT Thorax phantom, PinPoint ionization chamber, Gafchromic film, and bolus. Four clinical scenarios were evaluated: weight gain and weight loss were simulated by adding and removing bolus, internal target shifts were simulated by editing the CTV during the adaptive workflow to displace it, and changes in gas were simulated by removing and reinserting rods in varying phantom locations. The effect of overriding gas pockets during planning was also assessed. All point dose measurements agreed within 2.7% of the calculated dose, with one exception: a scenario simulating gas present in the planning CT, not overridden during planning, and dissipating at treatment. Relative film measurements passed gamma analysis (3%/3 mm criteria) for all scenarios. Our process validated the Ethos dose calculation for online adapted treatment plans. Based on our results, we made several recommendations for our clinical adaptive workflow. This commissioning process used commonly available equipment and, therefore, can be applied in other clinics for their respective online adaptive platforms.
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- 2022
17. Acceptability and Feasibility of a Mobile Phone Application to Support HIV Pre-exposure Prophylaxis Among Women with Opioid Use Disorder
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Richterman, Aaron, Ghadimi, Fatemeh, Teitelman, Anne M., Moore, Kevin, Acri, Trisha, North, Hannah, Lopez, Kasandra, Ou, Vuthy, Van Pelt, Amelia E., and Momplaisir, Florence
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- 2023
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18. Strong Sign Controllability of Diffusively-Coupled Networks
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Park, Nam-Jin, Kwon, Seong-Ho, Bae, Yoo-Bin, Kim, Byeong-Yeon, Moore, Kevin L., and Ahn, Hyo-Sung
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Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper presents several conditions to determine strong sign controllability for diffusively-coupled undirected networks. The strong sign controllability is determined by the sign patterns (positive, negative, zero) of the edges. We first provide the necessary and sufficient conditions for strong sign controllability of basic components, such as path, cycle, and tree. Next, we propose a merging process to extend the basic componenets to a larger graph based on the conditions of the strong sign controllability. Furthermore, we develop an algorithm of polynomial complexity to find the minimum number of external input nodes while maintaining the strong sign controllability of a network.
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- 2022
19. OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.
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Babier, Aaron, Mahmood, Rafid, Zhang, Binghao, Alves, Victor, Barragán-Montero, Ana, Beaudry, Joel, Cardenas, Carlos, Chang, Yankui, Chen, Zijie, Chun, Jaehee, Diaz, Kelly, David Eraso, Harold, Faustmann, Erik, Gaj, Sibaji, Gay, Skylar, Gronberg, Mary, Guo, Bingqi, He, Junjun, Heilemann, Gerd, Hira, Sanchit, Huang, Yuliang, Ji, Fuxin, Jiang, Dashan, Carlo Jimenez Giraldo, Jean, Lee, Hoyeon, Lian, Jun, Liu, Shuolin, Liu, Keng-Chi, Marrugo, José, Miki, Kentaro, Nakamura, Kunio, Netherton, Tucker, Nguyen, Dan, Nourzadeh, Hamidreza, Osman, Alexander, Peng, Zhao, Darío Quinto Muñoz, José, Ramsl, Christian, Joo Rhee, Dong, David Rodriguez, Juan, Shan, Hongming, Siebers, Jeffrey, Soomro, Mumtaz, Sun, Kay, Usuga Hoyos, Andrés, Valderrama, Carlos, Verbeek, Rob, Wang, Enpei, Willems, Siri, Wu, Qi, Xu, Xuanang, Yang, Sen, Yuan, Lulin, Zhu, Simeng, Zimmermann, Lukas, Moore, Kevin, Purdie, Thomas, McNiven, Andrea, and Chan, Theodore
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automated planning ,inverse optimization ,inverse problem ,knowledge-based planning ,open data ,optimization ,radiotherapy ,Humans ,Knowledge Bases ,Radiotherapy Dosage ,Radiotherapy Planning ,Computer-Assisted ,Radiotherapy ,Intensity-Modulated ,Reproducibility of Results - Abstract
Objective.To establish an open framework for developing plan optimization models for knowledge-based planning (KBP).Approach.Our framework includes radiotherapy treatment data (i.e. reference plans) for 100 patients with head-and-neck cancer who were treated with intensity-modulated radiotherapy. That data also includes high-quality dose predictions from 19 KBP models that were developed by different research groups using out-of-sample data during the OpenKBP Grand Challenge. The dose predictions were input to four fluence-based dose mimicking models to form 76 unique KBP pipelines that generated 7600 plans (76 pipelines × 100 patients). The predictions and KBP-generated plans were compared to the reference plans via: the dose score, which is the average mean absolute voxel-by-voxel difference in dose; the deviation in dose-volume histogram (DVH) points; and the frequency of clinical planning criteria satisfaction. We also performed a theoretical investigation to justify our dose mimicking models.Main results.The range in rank order correlation of the dose score between predictions and their KBP pipelines was 0.50-0.62, which indicates that the quality of the predictions was generally positively correlated with the quality of the plans. Additionally, compared to the input predictions, the KBP-generated plans performed significantly better (P< 0.05; one-sided Wilcoxon test) on 18 of 23 DVH points. Similarly, each optimization model generated plans that satisfied a higher percentage of criteria than the reference plans, which satisfied 3.5% more criteria than the set of all dose predictions. Lastly, our theoretical investigation demonstrated that the dose mimicking models generated plans that are also optimal for an inverse planning model.Significance.This was the largest international effort to date for evaluating the combination of KBP prediction and optimization models. We found that the best performing models significantly outperformed the reference dose and dose predictions. In the interest of reproducibility, our data and code is freely available.
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- 2022
20. Analytic Equation Sense: A Conceptual Model to Investigate Students' Algebraic Manipulation
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Ying, Yufeng and Moore, Kevin
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In this paper, I propose a new construct named "analytic equation sense" to conceptually model a desired way of reasoning that involves students' algebraic manipulations and use of equivalent expressions. Building from the analysis of two existing models in the field, I argue for the need for a new model and use empirical evidence to explain the new model. [For the complete proceedings, see ED630060.]
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- 2021
21. Classroom Supports for Generalizing
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Ellis, Amy, Ying, Yufeng, Wawsa, Anne, Moore, Kevin, Hamilton, Michael, Tasova, Halil I., and Çelik, Aytug Özaltun
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Generalization is a critical component of mathematics learning, but it can be challenging to foster generalization in classroom settings. Teachers need access to better tools and resources to teach for generalization, including an understanding of what tasks and pedagogical moves are most effective. This study identifies the types of instruction, student engagement, and enacted tasks that support generalizing in the classroom. We identified three categories of Classroom Supports for Generalizing (CSGs): Interactional Moves, Structuring Actions, and Instructional Routines. The three categories operate at different levels to show how teachers, students, tasks, and artifacts work in interaction to mutually support classroom generalizing. [For the complete proceedings, see ED630060.]
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- 2021
22. From Theory to Methodology: Guidance for Analyzing Students' Covariational Reasoning
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Tyburski, Brady A., Drimalla, James, Byerley, Cameron, Boyce, Steven, Grabhorn, Jeffrey, and Moore, Kevin C.
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The fields of quantitative and covariational reasoning boast a wide range of powerful theoretical tools, which are described carefully in the literature. Less frequent and explicit attention, however, has been paid to writing down detailed, practical guidance for operationalizing these theoretical constructs. Some guidance is provided by covariational reasoning frameworks, but much is left unsaid concerning the inherent complexities and ambiguities involved in analyzing students' moment-by-moment behaviors and what these behaviors convey about their covariational reasoning. In an effort to more clearly link theory to analytic methodology, we share three lessons about analyzing students' covariational reasoning to make research more accessible to newcomers and better address what is often left unsaid in the covariational reasoning literature. [For the complete proceedings, see ED630060.]
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- 2021
23. Investigating Elementary Pre-Service Teachers' Conceptions of Mathematical Creativity
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Waswa, Anne N. and Moore, Kevin C.
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Research in mathematics education has overlooked creativity in mathematics, partially because of a lack of an accepted definition of mathematical creativity. The present study investigates elementary pre-service teachers' (PSTs') conceptions of creativity in teaching and learning mathematics. Data were collected using observations and semi-structured interviews with nine PSTs and analyzed using thematic analysis. PSTs' conceptions of mathematical creativity included using multiple approaches to solve problems, designing mathematical tasks from scratch, making learning challenging but not impossible, and exercising independence in learning. Implications of these results are applicable to teacher preparation programs, and they suggest a need for more research on the nature of experience(s) that shapes PSTs' conceptions of mathematical creativity and how to develop it. [For the complete proceedings, see ED629884.]
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- 2020
24. An Invitation to Conversation: Addressing the Limitations of Graphical Tasks for Assessing Covariational Reasoning
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Drimalla, James, Tyburski, Brady A., Byerley, Cameron, Boyce, Steven, Grabhorn, Jeffrey, Roman, Christopher Orlando, and Moore, Kevin C.
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We reflect on the limitations of our research group's prior methods for assessing covariational reasoning which primarily used graphical tasks found in extant literature. Graphical tasks dominate the literature on covariational reasoning, and through our use of these tasks we came to question the heavy reliance on them. Our concerns led us to ask the following: (1) What are the limitations of using tasks with graphs to assess covariational reasoning? (2) How can we improve assessment of covariational reasoning to accommodate students with nonnormative graphing schemes? We offer this piece as the beginning of a conversation to develop improved methodologies that attend to the ubiquity of students' nonnormative graphing schemes. [For the complete proceedings, see ED629884.]
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- 2020
25. Framework for Representing a Multiplicative Object in the Context of Graphing
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Tasova, Halil I. and Moore, Kevin C.
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In this study, based on the analysis of a teaching experiment with middle school students, we propose a framework for describing meanings of a point represented on a plane in terms of multiplicative objects in the context of graphing. We classify those meanings as representing: (1) non-multiplicative objects; (2) quantitative multiplicative objects (Type-1 and Type 2); and (3) spatial multiplicative objects. We then discuss implications of these meanings with respect to students' graphing activities. [For the complete proceedings, see ED629884.]
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- 2020
26. Knowledge-based three-dimensional dose prediction for tandem-and-ovoid brachytherapy.
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Cortes, Katherina G, Kallis, Karoline, Simon, Aaron, Mayadev, Jyoti, Meyers, Sandra M, and Moore, Kevin L
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Humans ,Tomography ,X-Ray Computed ,Brachytherapy ,Radiotherapy Dosage ,Radiotherapy Planning ,Computer-Assisted ,Uterine Cervical Neoplasms ,Female ,Organs at Risk ,Cervical cancer ,Convolutional neural network ,Deep learning ,Knowledge-based dose estimation ,Knowledge-based planning ,Tandem and ovoids ,Knowledge -based plan ,Clinical Sciences ,Oncology & Carcinogenesis - Abstract
PurposeThe purpose of this work was to develop a knowledge-based dose prediction system using a convolution neural network (CNN) for cervical brachytherapy treatments with a tandem-and-ovoid applicator.MethodsA 3D U-NET CNN was utilized to make voxel-wise dose predictions based on organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source location geometry. The model comprised 395 previously treated cases: training (273), validation (61), test (61). To assess voxel prediction accuracy, we evaluated dose differences in all cohorts across the dose range of 20-130% of prescription, mean (SD) and standard deviation (σ), as well as isodose dice similarity coefficients for clinical and/or predicted dose distributions. We examined discrete Dose-Volume Histogram (DVH) metrics utilized for brachytherapy plan quality assessment (HRCTV D90%; bladder, rectum, and sigmoid D2cc) with ΔDx=Dx,actual-Dx,predicted mean, standard deviation, and Pearson correlation coefficient further quantifying model performance.ResultsRanges of voxel-wise dose difference accuracy (δD¯±σ) for 20-130% dose interval in training (test) sets ranged from [-0.5% ± 2.0% to +2.0% ± 14.0%] ([-0.1% ± 4.0% to +4.0% ± 26.0%]) in all voxels, [-1.7% ± 5.1% to -3.5% ± 12.8%] ([-2.9% ± 4.8% to -2.6% ± 18.9%]) in HRCTV, [-0.02% ± 2.40% to +3.2% ± 12.0%] ([-2.5% ± 3.6% to +0.8% ± 12.7%]) in bladder, [-0.7% ± 2.4% to +15.5% ± 11.0%] ([-0.9% ± 3.2% to +27.8% ± 11.6%]) in rectum, and [-0.7% ± 2.3% to +10.7% ± 15.0%] ([-0.4% ± 3.0% to +18.4% ± 11.4%]) in sigmoid. Isodose dice similarity coefficients ranged from [0.96,0.91] for training and [0.94,0.87] for test cohorts. Relative DVH metric prediction in the training (test) set were HRCTV ΔD¯90±σΔD = -0.19 ± 0.55Gy (-0.09 ± 0.67 Gy), bladder ΔD¯2cc±σΔD = -0.06 ± 0.54Gy (-0.17 ± 0.67 Gy), rectum ΔD¯2cc±σΔD= -0.03 ± 0.36Gy (-0.04 ± 0.46 Gy), and sigmoid ΔD¯2cc±σΔD = -0.01 ± 0.34Gy (0.00 ± 0.44 Gy).ConclusionsA 3D knowledge-based dose predictions provide voxel-level and DVH metric estimates that could be used for treatment plan quality control and data-driven plan guidance.
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- 2022
27. Using Scorecards to Tune Ethos Directive Templates: An Adaptive Radiation Therapy Individualized Approach-Cervix Dosimetric Planning Study
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Rayn, Kareem, Magliari, Anthony, Clark, Ryan, Rana, Omar, Moore, Kevin, and Ray, Xenia
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- 2024
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28. Using abstraction to analyze instructional tasks and their implementation
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Moore, Kevin C., Wood, Erin, Welji, Shaffiq, Hamilton, Mike, Waswa, Anne, Ellis, Amy B., and Tasova, Halil I.
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- 2024
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29. AlcoChange: A digital therapeutic for patients with alcohol-related liver disease
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Mehta, Gautam, Lin, Su, Nadar, Aida, PV, Bharadwaj, Kumar, Ravi, Balaji, Anu, Macdonald, Stewart, Sheikh, Mohammed F., Saeidinejad, MohammadMahdi, Sharma, Shiv-Raj, King, Ji J., Mookerjee, Rajeshwar P., McDonagh, Lorraine, Afuwape, Sarah A., Moore, Kevin, and Jalan, Rajiv
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- 2024
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30. Social and demographic factors associated with differences in skin self-examination practices for skin cancer detection
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Desai, Sheena, Moore, Kevin J, Trepanowski, Nicole, and Hartman, Rebecca I
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cancer ,examination ,prevention ,self ,skin - Published
- 2022
31. End of treatment cone-beam computed tomography (CBCT) is predictive of radiation response and overall survival in oropharyngeal squamous cell carcinoma
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Sumner, Whitney, Kim, Sangwoo S, Vitzthum, Lucas, Moore, Kevin, Atwood, Todd, Murphy, James, Miyauchi, Sayuri, Califano, Joseph A, Mell, Loren K, Mundt, Arno J, and Sharabi, Andrew B
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Rare Diseases ,Cancer ,Biomedical Imaging ,Clinical Research ,Dental/Oral and Craniofacial Disease ,Detection ,screening and diagnosis ,4.2 Evaluation of markers and technologies ,Adult ,Aged ,Aged ,80 and over ,Carcinoma ,Squamous Cell ,Cone-Beam Computed Tomography ,Female ,Follow-Up Studies ,Humans ,Image Processing ,Computer-Assisted ,Male ,Middle Aged ,Organs at Risk ,Oropharyngeal Neoplasms ,Prognosis ,Radiotherapy Dosage ,Radiotherapy Planning ,Computer-Assisted ,Radiotherapy ,Image-Guided ,Radiotherapy ,Intensity-Modulated ,Retrospective Studies ,Survival Rate ,Head and neck squamous cell carcinoma ,Head and neck cancer ,Radiotherapy ,Radiation ,Cone beam CT ,CBCT ,Oncology and Carcinogenesis ,Oncology & Carcinogenesis - Abstract
BackgroundImage guidance in radiation oncology has resulted in significant improvements in the accuracy and precision of radiation therapy (RT). Recently, the resolution and quality of cone beam computed tomography (CBCT) for image guidance has increased so that tumor masses and lymph nodes are readily detectable and measurable. During treatment of head and neck squamous cell carcinoma (HNSCC), on-board CBCT setup imaging is routinely obtained; however, this CBCT imaging data is not utilized to predict patient outcomes. Here, we analyzed whether changes in CBCT measurements obtained during a course of radiation therapy correlate with responses on routine 3-month follow-up diagnostic imaging and overall survival (OS).Materials/methodsPatients with oropharyngeal primary tumors who received radiation therapy between 2015 and 2018 were included. Anatomical measurements were collected of largest nodal conglomerate (LNC) at CT simulation, end of radiation treatment (EOT CBCT), and routine 3-month post-RT imaging. At each timepoint anteroposterior (AP), mediolateral (ML) and craniocaudal (CC) measurements were obtained and used to create a 2-dimensional (2D) maximum.ResultsCBCT data from 64 node positive patients were analyzed. The largest nodal 2D maximum and CC measurements on EOT CBCT showed a statistically significant correlation with complete response on 3-month post-RT imaging (r = 0.313, p = 0.02 and r = 0.318, p = 0.02, respectively). Furthermore, patients who experienced a 30% or greater reduction in the CC dimension had improved OS (Binary Chi-Square HR 4.85, p = 0.028).ConclusionDecreased size of pathologic lymph nodes measured using CBCT setup imaging during a radiation course correlates with long term therapeutic response and overall survival of HNSCC patients. These results indicate that CBCT setup imaging may have utility as an early predictor of treatment response in oropharyngeal HNSCC.
- Published
- 2021
32. Topological approach and analysis of clustering in consensus networks
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Ma, Jeong-Min, Lee, Hyung-Gon, Ahn, Hyo-Sung, Moore, Kevin L., and Oh, Kwang-Kyo
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- 2024
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33. Knowledge-Based Three-Dimensional Dose Prediction for Tandem-And-Ovoid Brachytherapy
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Cortes, Katherina G., Simon, Aaron, Kallis, Karoline, Mayadev, Jyoti, Meyers, Sandra, and Moore, Kevin L.
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Physics - Medical Physics - Abstract
Purpose: To develop a knowledge-based voxel-wise dose prediction system using a convolution neural network for high-dose-rate brachytherapy cervical cancer treatments with a tandem-and-ovoid (T&O) applicator. Methods: A 3D U-NET was utilized to output dose predictions using organ-at-risk (OAR), high-risk clinical target volume (HRCTV), and possible source locations. A sample of previous T&O treatments comprising 397 cases (273 training:62 validation:62 test), HRCTV and OARs (bladder/rectum/sigmoid) was used. Structures and dose were interpolated to 1x1x2.5mm3 dose planes with two input channels (source positions, voxel identification) and one output channel for dose. We evaluated dose difference (\Delta D)(xyz)=D_(actual)(x,y,z)-D_(predicted)(x,y,z) and dice similarity coefficients in all cohorts across the clinically-relevant dose range (20-130% of prescription), mean and standard deviation. We also examined discrete DVH metrics used for T&O plan quality assessment: HRCTV D_90%(dose to hottest 90% volume) and OAR D_2cc, with \Delta D_x=D_(x,actual)-D_(x,predicted). Pearson correlation coefficient, standard deviation, and mean quantified model performance on the clinical metrics. Results: Voxel-wise dose difference accuracy for 20-130% dose range for training(test) ranges for mean (\Delta D) and standard deviation for all voxels was [-0.3%+/-2.0% to +1.0%+/-12.0%] ([-0.1%+/-4% to +4.0%+/-26%]). Voxel-wise dice similarity coefficients for 20-130% dose ranged from [0.96, 0.91]([0.94, 0.87]). DVH metric prediction in the training (test) set were HRCTV(\Delta D_90)=-0.19+/-0.55 Gy (-0.09+/-0.67 Gy), bladder(\Delta D_2cc)=-0.06+/-0.54 Gy (-0.17+/-0.67 Gy), rectum(\Delta D)_2cc=-0.03+/-0.36 Gy (-0.04+/-0.46 Gy), and sigmoid(\Delta D_2cc)=-0.01+/-0.34 Gy (0.00+/-0.44 Gy). Conclusion: 3D knowledge-based dose predictions for T&O brachytherapy provide accurate voxel-level and DVH metric estimates.
- Published
- 2021
34. Knowledge-based dose prediction models to inform gynecologic brachytherapy needle supplementation for locally advanced cervical cancer
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Kallis, Karoline, Mayadev, Jyoti, Kisling, Kelly, Brown, Derek, Scanderbeg, Daniel, Ray, Xenia, Cortes, Katherina, Simon, Aaron, Yashar, Catheryn M, Einck, John P, Mell, Loren K, Moore, Kevin L, and Meyers, Sandra M
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Cancer ,Brachytherapy ,Dietary Supplements ,Female ,Humans ,Needles ,Radiotherapy Dosage ,Uterine Cervical Neoplasms ,knowledge-based ,Dose prediction ,Cervix cancer ,Needle supplementation ,Clinical Sciences ,Oncology & Carcinogenesis ,Clinical sciences - Abstract
PurposeThe use of interstitial needles, combined with intracavitary applicators, enables customized dose distributions and is beneficial for complex cases, but increases procedure time. Overall, applicator selection is not standardized and depends on physician expertise and preference. The purpose of this study is to determine whether dose prediction models can guide needle supplementation decision-making for cervical cancer.Materials and methodsIntracavitary knowledge-based models for organ-at-risk (OAR) dose estimation were trained and validated for tandem-and-ring/ovoids (T&R/T&O) implants. Models were applied to hybrid cases with 1-3 implanted needles to predict OAR dose without needles. As a reference, 70/67 hybrid T&R/T&O cases were replanned without needles, following a standardized procedure guided by dose predictions. If a replanned dose exceeded the dose objective, the case was categorized as requiring needles. Receiver operating characteristic (ROC) curves of needle classification accuracy were generated. Optimal classification thresholds were determined from the Youden Index.ResultsNeedle supplementation reduced dose to OARs. However, 67%/39% of replans for T&R/T&O met all dose constraints without needles. The ROC for T&R/T&O models had an area-under-curve of 0.89/0.86, proving high classification accuracy. The optimal threshold of 99%/101% of the dose limit for T&R/T&O resulted in classification sensitivity and specificity of 78%/86% and 85%/78%.ConclusionsNeedle supplementation reduced OAR dose for most cases but was not always required to meet standard dose objectives, particularly for T&R cases. Our knowledge-based dose prediction model accurately identified cases that could have met constraints without needle supplementation, suggesting that such models may be beneficial for applicator selection.
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- 2021
35. Evaluation of dose differences between intracavitary applicators for cervical brachytherapy using knowledge-based models
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Kallis, Karoline, Mayadev, Jyoti, Covele, Brent, Brown, Derek, Scanderbeg, Daniel, Simon, Aaron, Frisbie-Firsching, Helena, Yashar, Catheryn M, Einck, John P, Mell, Loren K, Moore, Kevin L, and Meyers, Sandra M
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Cancer ,Cervical Cancer ,Clinical Research ,Urologic Diseases ,Good Health and Well Being ,Brachytherapy ,Female ,Humans ,Organs at Risk ,Radiotherapy Dosage ,Radiotherapy Planning ,Computer-Assisted ,Rectum ,Uterine Cervical Neoplasms ,Knowledge-based planning ,Dose prediction ,Cervical cancer ,Intracavitary brachytherapy ,Tandem and ovoids ,Tandem and ring ,Clinical Sciences ,Oncology & Carcinogenesis ,Clinical sciences - Abstract
PurposeCurrently, there is a lack of patient-specific tools to guide brachytherapy planning and applicator choice for cervical cancer. The purpose of this study is to evaluate the accuracy of organ-at-risk (OAR) dose predictions using knowledge-based intracavitary models, and the use of these models and clinical data to determine the dosimetric differences of tandem-and-ring (T&R) and tandem-and-ovoids (T&O) applicators.Materials and methodsKnowledge-based models, which predict organ D2cc, were trained on 77/75 cases and validated on 32/38 for T&R/T&O applicators. Model performance was quantified using ΔD2cc=D2cc,actual-D2cc,predicted, with standard deviation (σ(ΔD2cc)) representing precision. Model-predicted applicator dose differences were determined by applying T&O models to T&R cases, and vice versa, and compared to clinically-achieved D2cc differences. Applicator differences were assessed using a Student's t-test (p < 0.05 significant).ResultsValidation T&O/T&R model precision was 0.65/0.55 Gy, 0.55/0.38 Gy, and 0.43/0.60 Gy for bladder, rectum and sigmoid, respectively, and similar to training. When applying T&O/T&R models to T&R/T&O cases, bladder, rectum and sigmoid D2cc values in EQD2 were on average 5.69/2.62 Gy, 7.31/6.15 Gy and 3.65/0.69 Gy lower for T&R, with similar HRCTV volume and coverage. Clinical data also showed lower T&R OAR doses, with mean EQD2 D2cc deviations of 0.61 Gy, 7.96 Gy (p < 0.01) and 5.86 Gy (p < 0.01) for bladder, rectum and sigmoid.ConclusionsAccurate knowledge-based dose prediction models were developed for two common intracavitary applicators. These models could be beneficial for standardizing and improving the quality of brachytherapy plans. Both models and clinical data suggest that significant OAR sparing can be achieved with T&R over T&O applicators, particularly for the rectum.
- Published
- 2021
36. Computational ECG mapping and respiratory gating to optimize stereotactic ablative radiotherapy workflow for refractory ventricular tachycardia.
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Ho, Gordon, Atwood, Todd F, Bruggeman, Andrew R, Moore, Kevin L, McVeigh, Elliot, Villongco, Christopher T, Han, Frederick T, Hsu, Jonathan C, Hoffmayer, Kurt S, Raissi, Farshad, Lin, Grace Y, Schricker, Amir, Woods, Christopher E, Cheung, Joey P, Taira, Al V, McCulloch, Andrew, Birgersdotter-Green, Ulrika, Feld, Gregory K, Mundt, Arno J, and Krummen, David E
- Subjects
Ablation ,Cardiac computed tomography ,Electrocardiography ,Noninvasive mapping ,Stereotactic ablative radiotherapy ,Ventricular tachycardia ,Clinical Research ,Cardiovascular ,Heart Disease ,Good Health and Well Being - Abstract
BackgroundStereotactic ablative radiotherapy (SAbR) is an emerging therapy for refractory ventricular tachycardia (VT). However, the current workflow is complicated, and the precision and safety in patients with significant cardiorespiratory motion and VT targets near the stomach may be suboptimal.ObjectiveWe hypothesized that automated 12-lead electrocardiogram (ECG) mapping and respiratory-gated therapy may improve the ease and precision of SAbR planning and facilitate safe radiation delivery in patients with refractory VT.MethodsConsecutive patients with refractory VT were studied at 2 hospitals. VT exit sites were localized using a 3-D computational ECG algorithm noninvasively and compared to available prior invasive mapping. Radiotherapy (25 Gy) was delivered at end-expiration when cardiac respiratory motion was ≥0.6 cm or targets were ≤2 cm from the stomach.ResultsIn 6 patients (ejection fraction 29% ± 13%), 4.2 ± 2.3 VT morphologies per patient were mapped. Overall, 7 out of 7 computational ECG mappings (100%) colocalized to the identical cardiac segment when prior invasive electrophysiology study was available. Respiratory gating was associated with smaller planning target volumes compared to nongated volumes (71 ± 7 vs 153 ± 35 cc, P < .01). In 2 patients with inferior wall VT targets close to the stomach (6 mm proximity) or significant respiratory motion (22 mm excursion), no GI complications were observed at 9- and 12-month follow-up. Implantable cardioverter-defibrillator shocks decreased from 23 ± 12 shocks/patient to 0.67 ± 1.0 (P < .001) post-SAbR at 6.0 ± 4.9 months follow-up.ConclusionsA workflow including computational ECG mapping and protocol-guided respiratory gating is feasible, is safe, and may improve the ease of SAbR planning. Studies to validate this workflow in larger populations are required.
- Published
- 2021
37. OpenKBP: The open-access knowledge-based planning grand challenge
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Babier, Aaron, Zhang, Binghao, Mahmood, Rafid, Moore, Kevin L., Purdie, Thomas G., McNiven, Andrea L., and Chan, Timothy C. Y.
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Physics - Medical Physics ,Computer Science - Computer Vision and Pattern Recognition - Abstract
The purpose of this work is to advance fair and consistent comparisons of dose prediction methods for knowledge-based planning (KBP) in radiation therapy research. We hosted OpenKBP, a 2020 AAPM Grand Challenge, and challenged participants to develop the best method for predicting the dose of contoured CT images. The models were evaluated according to two separate scores: (1) dose score, which evaluates the full 3D dose distributions, and (2) dose-volume histogram (DVH) score, which evaluates a set DVH metrics. Participants were given the data of 340 patients who were treated for head-and-neck cancer with radiation therapy. The data was partitioned into training (n=200), validation (n=40), and testing (n=100) datasets. All participants performed training and validation with the corresponding datasets during the validation phase of the Challenge, and we ranked the models in the testing phase based on out-of-sample performance. The Challenge attracted 195 participants from 28 countries, and 73 of those participants formed 44 teams in the validation phase, which received a total of 1750 submissions. The testing phase garnered submissions from 28 teams. On average, over the course of the validation phase, participants improved the dose and DVH scores of their models by a factor of 2.7 and 5.7, respectively. In the testing phase one model achieved significantly better dose and DVH score than the runner-up models. Lastly, many of the top performing teams reported using generalizable techniques (e.g., ensembles) to achieve higher performance than their competition. This is the first competition for knowledge-based planning research, and it helped launch the first platform for comparing KBP prediction methods fairly and consistently. The OpenKBP datasets are available publicly to help benchmark future KBP research, which has also democratized KBP research by making it accessible to everyone., Comment: 26 pages, 6 figures, 5 tables
- Published
- 2020
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38. Exploring Relative Size with Relative Risk
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Joshua, Surani, Drimalla, James, Horne, Dru, Lavender, Heather, Yon, Alexandra, Byerley, Cameron, Yoon, Hyunkyoung, and Moore, Kevin
- Abstract
To facilitate people using mathematical reasoning to compare risks associated with the COVID-19 pandemic, the National Science Foundation (NSF) funded the COViD-TASER (Creation of Visualizations of Data: The Application of STEM Education Research) research team to create the COVID-19 Relative Risk Tool (RRT). The RRT uses an interactive bar chart to display COVID-19 infection and vaccination risks alongside more familiar risks like driving, contracting breast cancer, playing soccer, and skydiving. To involve students, the authors developed and tested elementary, middle, and high school lesson plans that use the RRT. Each lesson is aligned with the Common Core State Standards for Mathematics (CCSSM; NGA Center and CCSSO 2010) for both content and mathematical practice, and each plan pursues two goals: (1) making comparisons of relative size of quantities, and (2) interpreting these relative sizes to understand COVID-19 data. For teachers who wish to incorporate more real-world contexts in the mathematics classroom and are unsure of how to start, the authors hope that their structured, pretested lessons plans provide a starting place for to help students make connections between the classroom and their everyday lives.
- Published
- 2022
39. Evaluating the Efficacy of the Family Check-Up Online: A School-Based, eHealth Model for the Prevention of Problem Behavior during the Middle School Years
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Stormshak, Elizabeth A., Seeley, John R., Caruthers, Allison S., Cardenas, Lucia, Moore, Kevin J., Tyler, Milagra S., Fleming, Christopher M., Gau, Jeff, and Danaher, Brian
- Abstract
This study evaluated the efficacy of a family-centered preventive intervention, the Family Check-Up (FCU), delivered as an online, eHealth model to middle school families. To increase accessibility of family-centered prevention in schools, we adapted the evidence-based FCU to an online format, with the goal of providing a model of service delivery that is feasible, given limited staffing and resources in many schools. Building on prior research, we randomly assigned participants to waitlist control (n = 105), FCU Online as a web-based intervention (n = 109), and FCU Online with coaching support (n = 108). We tested the effects of the intervention on multiple outcomes, including parental self-efficacy, child self-regulation, and child behavior, in this registered clinical trial (NCT03060291). Families engaged in the intervention at a high rate (72% completed the FCU assessment) and completed 3-month post-test assessments with good retention (94% retained). Random assignment to the FCU Online with coaching support was associated with reduced emotional problems for children (p = 0.003, d = -0.32) and improved parental confidence and self-efficacy (p = 0.018, d = 0.25) when compared with waitlist controls. Risk moderated effects: at-risk youth showed stronger effects than did those with minimal risk. The results have implications for online delivery of family-centered interventions in schools. [This paper was published in "Development and Psychopathology" v31 n5 p1873-1886 2019.]
- Published
- 2019
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40. Systematically derived thermodynamic properties for alkane oxidation
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Elliott, Sarah N., Moore, Kevin B., III, Copan, Andreas V., Georgievskii, Yuri, Keçeli, Murat, Somers, Kieran P., Ghosh, Manik K., Curran, Henry J., and Klippenstein, Stephen J.
- Published
- 2023
- Full Text
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41. Automated identification and calculation of prompt effects in kinetic mechanisms using statistical models
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Pratali Maffei, Luna, Moore, Kevin B., III, Georgievskii, Yuri, Mulvihill, Clayton R., Elliott, Sarah N., Cho, Jaeyoung, Sivaramakrishnan, Raghu, Faravelli, Tiziano, and Klippenstein, Stephen J.
- Published
- 2023
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42. Yoorrook: truth telling in the Victorian Treaty process
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Moore, Kevin James, primary, Stanton, Pauline, additional, Fan, Shea X., additional, Rose, Mark, additional, and Jones, Mark, additional
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- 2024
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43. THU-074 Effect of terlipressin on patients with hepatorenal syndrome, alcohol-associated hepatitis, and acute-on-chronic liver failure grade 0–2
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Moore, Kevin, primary, Grewal, Priya, additional, Olivera, Marco, additional, Bari, Khurram, additional, and Jamil, Khurram, additional
- Published
- 2024
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44. Climate Change Mitigation, Adaptation, and Resilience: Challenges and Opportunities for the Control Systems Community
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Khargonekar, Pramod P., primary, Samad, Tariq, additional, Amin, Saurabh, additional, Chakrabortty, Aranya, additional, Dabbene, Fabrizio, additional, Das, Amritam, additional, Fujita, Masayuki, additional, Garcia-Sanz, Mario, additional, Gayme, Dennice F., additional, Ilić, Marija, additional, Mareels, Iven, additional, Moore, Kevin L., additional, Pao, Lucy Y., additional, Rajhans, Akshay, additional, Stoustrup, Jakob, additional, Zafar, Junaid, additional, and Bauer, Margret, additional
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- 2024
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45. Generalization across Multiple Mathematical Domains: Relating, Forming, and Extending
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Ellis, Amy B., Lockwood, Elise, Tillema, Erik, and Moore, Kevin
- Abstract
Generalization is a critical component of mathematical reasoning, with researchers recommending that it be central to education at all grade levels. However, research on students' generalizing reveals pervasive difficulties in creating and expressing general statements, which underscores the need to better understand the processes that can support more productive generalizations. In response, we report on results from 146 interviews with 93 participants in middle school through college in the domains of algebra, advanced algebra, trigonometry/pre-calculus, and combinatorics while solving complex problems. Our findings yielded the Relating-Forming-Extending (RFE) Framework, which distinguishes multiple related forms and types of generalizing. We also present two aspects of mental activity that promote generative generalizations: operative activity, and building and refining activity.
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- 2022
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46. Promoting Family Centered Support Assessment and Intervention
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Garbacz, S. Andrew, Moore, Kevin J., Mauricio, Anne M., and Stormshak, Elizabeth A.
- Abstract
This paper describes a new paradigm for addressing threats of school violence. We advance a family-centered approach to supporting students to address the contextual characteristics of school violence and promote collaboration among families, school personnel, and students. We present a case study that demonstrate the utility of this family-centered approach. We conclude by articulating practice and research implications for using this family-centered approach as a primary avenue to increase school and community safety and to improve social-emotional outcomes for students.
- Published
- 2022
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47. Promoting Family-Centered Support Assessment and Intervention to Enhance School Climate
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Garbacz, S. Andrew, Moore, Kevin A., Mauricio, Anne Marie, and Stormshak, Elizabeth A.
- Abstract
This paper describes a new paradigm for addressing threats of school violence. We advance a family-centered approach to supporting students to address the contextual characteristics of school violence and promote collaboration among families, school personnel, and students. We present a case study that demonstrate the utility of this family-centered approach. We conclude by articulating practice and research implications for using this family-centered approach as a primary avenue to increase school and community safety and to improve social-emotional outcomes for students. [This paper was published in "Journal of Educational and Psychological Consultation" v32 n2 p185-209 2022 (EJ1344976).]
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- 2022
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48. The Audacity of Authenticity: Personal and Professional Identity Negotiation in Queer Preservice Teachers
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Moore, Kevin M.
- Abstract
The purpose of this study was to examine the intersection of preservice teachers' personal identities as queer individuals with their emerging professional identities as educators. Political and social environments contribute to a separation of these identities, which can further the marginalization of these individuals to the detriment of both their identities as people as well as their professional practice. Guided by a theoretical framework of figured worlds, interviews with students in teacher education programs that identify as queer explore the ways in which unique confluences of contextualizing factors play a role in the lived experiences of these individuals. The study additionally examined the nature of teacher education programs as experienced by these participants in order to discuss the ways in which these programs serve to challenge or reinforce the heteronormativity pervasive in educational spaces. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
- Published
- 2022
49. Automated contouring and planning pipeline for hippocampal-avoidant whole-brain radiotherapy
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Feng, Christine H, Cornell, Mariel, Moore, Kevin L, Karunamuni, Roshan, and Seibert, Tyler M
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Cancer ,Neurosciences ,Clinical Research ,Adult ,Artificial Intelligence ,Brain Neoplasms ,Cranial Irradiation ,Hippocampus ,Humans ,Organs at Risk ,Radiotherapy Planning ,Computer-Assisted ,Retrospective Studies ,Brain metastases ,Hippocampal-avoidant whole-brain radiotherapy ,Artificial intelligence ,Radiotherapy automation ,Brain segmentation ,Knowledge-based planning ,Oncology and Carcinogenesis ,Oncology & Carcinogenesis - Abstract
BackgroundWhole-brain radiotherapy (WBRT) remains an important treatment for over 200,000 cancer patients in the United States annually. Hippocampal-avoidant WBRT (HA-WBRT) reduces neurocognitive toxicity compared to standard WBRT, but HA-WBRT contouring and planning are more complex and time-consuming than standard WBRT. We designed and evaluated a workflow using commercially available artificial intelligence tools for automated hippocampal segmentation and treatment planning to efficiently generate clinically acceptable HA-WBRT radiotherapy plans.MethodsWe retrospectively identified 100 consecutive adult patients treated for brain metastases outside the hippocampal region. Each patient's T1 post-contrast brain MRI was processed using NeuroQuant, an FDA-approved software that provides segmentations of brain structures in less than 8 min. Automated hippocampal segmentations were reviewed for accuracy, then converted to files compatible with a commercial treatment planning system, where hippocampal avoidance regions and planning target volumes (PTV) were generated. Other organs-at-risk (OARs) were previously contoured per clinical routine. A RapidPlan knowledge-based planning routine was applied for a prescription of 30 Gy in 10 fractions using volumetric modulated arc therapy (VMAT) delivery. Plans were evaluated based on NRG CC001 dose-volume objectives (Brown et al. in J Clin Oncol, 2020).ResultsOf the 100 cases, 99 (99%) had acceptable automated hippocampi segmentations without manual intervention. Knowledge-based planning was applied to all cases; the median processing time was 9 min 59 s (range 6:53-13:31). All plans met per-protocol dose-volume objectives for PTV per the NRG CC001 protocol. For comparison, only 65.5% of plans on NRG CC001 met PTV goals per protocol, with 26.1% within acceptable variation. In this study, 43 plans (43%) met OAR constraints, and the remaining 57 (57%) were within acceptable variation, compared to 42.5% and 48.3% on NRG CC001, respectively. No plans in this study had unacceptable dose to OARs, compared to 0.8% of manually generated plans from NRG CC001. 8.4% of plans from NRG CC001 were not scored or unable to be evaluated.ConclusionsAn automated pipeline harnessing the efficiency of commercially available artificial intelligence tools can generate clinically acceptable VMAT HA-WBRT plans with minimal manual intervention. This process could improve clinical efficiency for a treatment established to improve patient outcomes over standard WBRT.
- Published
- 2020
50. No difference in survival for primary cutaneous Merkel cell carcinoma after Mohs micrographic surgery and wide local excision
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Moore, Kevin J., Thakuria, Manisha, and Ruiz, Emily S.
- Published
- 2023
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