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1. Investigating and improving student understanding of the basics of quantum computing

Author

Hu, Peter, Li, Yangqiuting, and Singh, Chandralekha

Subjects
Physics - Physics Education
Abstract

Quantum information science and engineering (QISE) is a rapidly developing field that leverages the skills of experts from many disciplines to utilize the potential of quantum systems in a variety of applications. It requires talent from a wide variety of traditional fields, including physics, engineering, chemistry, and computer science, to name a few. To prepare students for such opportunities, it is important to give them a strong foundation in the basics of QISE, in which quantum computing plays a central role. In this study, we discuss the development, validation, and evaluation of a QuILT, or Quantum Interactive Learning Tutorial, on the basics and applications of quantum computing. These include an overview of key quantum mechanical concepts relevant for quantum computation (including ways a quantum computer is different from a classical computer), properties of single- and multi-qubit systems, and the basics of single-qubit quantum gates. The tutorial uses guided inquiry-based teaching-learning sequences. Its development and validation involved conducting cognitive task analysis from both expert and student perspectives and using common student difficulties as a guide. The inquiry-based learning sequences in the tutorial provide scaffolding support to help students develop a functional understanding. The final version of the validated tutorial was implemented in two distinct courses offered by the physics department with slightly different student populations and broader course goals. Students' understanding was evaluated after traditional lecture-based instruction on the requisite concepts, and again after engaging with the tutorial. We analyze and discuss their improvement in performance on concepts covered in the tutorial., Comment: 39 pages

Published
2024
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2. The Mysterious Case of Neuron 1512: Injectable Realignment Architectures Reveal Internal Characteristics of Meta's Llama 2 Model

Author

Smith, Brenden, Baker, Dallin, Chase, Clayton, Barney, Myles, Parker, Kaden, Allred, Makenna, Hu, Peter, Evans, Alex, and Fulda, Nancy

Subjects
Computer Science - Computation and Language
Abstract

Large Language Models (LLMs) have an unrivaled and invaluable ability to "align" their output to a diverse range of human preferences, by mirroring them in the text they generate. The internal characteristics of such models, however, remain largely opaque. This work presents the Injectable Realignment Model (IRM) as a novel approach to language model interpretability and explainability. Inspired by earlier work on Neural Programming Interfaces, we construct and train a small network -- the IRM -- to induce emotion-based alignments within a 7B parameter LLM architecture. The IRM outputs are injected via layerwise addition at various points during the LLM's forward pass, thus modulating its behavior without changing the weights of the original model. This isolates the alignment behavior from the complex mechanisms of the transformer model. Analysis of the trained IRM's outputs reveals a curious pattern. Across more than 24 training runs and multiple alignment datasets, patterns of IRM activations align themselves in striations associated with a neuron's index within each transformer layer, rather than being associated with the layers themselves. Further, a single neuron index (1512) is strongly correlated with all tested alignments. This result, although initially counterintuitive, is directly attributable to design choices present within almost all commercially available transformer architectures, and highlights a potential weak point in Meta's pretrained Llama 2 models. It also demonstrates the value of the IRM architecture for language model analysis and interpretability. Our code and datasets are available at https://github.com/DRAGNLabs/injectable-alignment-model, Comment: 21 pages, 17 figures

Published
2024

4. Student Understanding of the Bloch Sphere

Author

Hu, Peter, Li, Yangqiuting, Mong, Roger S. K., and Singh, Chandralekha

Subjects
Physics - Physics Education
Abstract

Quantum information science is a rapidly growing interdisciplinary field that is attracting the attention of academics and industry experts alike. It requires talent from a wide variety of traditional fields, including physics, engineering, chemistry, and computer science, to name a few. To prepare students for such opportunities, it is important to give them a strong foundation in the basics of quantum information science, in which quantum computing plays a central role. In this study, we discuss the development, validation, and evaluation of a tutorial on the Bloch sphere, a useful visual tool for developing intuition about single quantum bits (qubits), which are the basic building block of any quantum computer. Students' understanding was evaluated after they received traditional lecture-based instruction on the requisite topics, and again after engaging with the tutorial. We observe, analyze, and discuss their improvement in performance on concepts covered in the tutorial., Comment: 19 pages, 1 figure

Published
2024
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5. Challenges in addressing student difficulties with measurement uncertainty of two-state quantum systems using a multiple-choice question sequence in online and in-person classes

Author

Hu, Peter, Li, Yangqiuting, and Singh, Chandralekha

Subjects
Physics - Physics Education
Abstract

Research-validated multiple-choice questions comprise an easy-to-implement instructional tool that serves to scaffold student learning and formatively assess students knowledge. We present findings from the implementation, in consecutive years, of research-validated multiple-choice question sequence on measurement uncertainty as it applies to two-state quantum systems. This study was conducted in an advanced undergraduate quantum mechanics course, in an online and in-person learning environments in consecutive years. Student learning was assessed after receiving traditional lecture-based instruction in relevant concepts, and their performance was compared with that on a similar assessment given after engaging with the multiple-choice question sequence. We analyze and discuss the similar and differing trends observed in the two modes of instruction., Comment: 23 pages, 0 figures

Published
2024
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6. Challenges in addressing student difficulties with quantum measurement of two-state quantum systems using a multiple-choice question sequence in online and in-person classes

Author

Hu, Peter, Li, Yangqiuting, and Singh, Chandralekha

Subjects
Physics - Physics Education
Abstract

Research-validated multiple-choice questions comprise an easy-to-implement instructional tool that serves to scaffold student learning and formatively assess students' knowledge. We present findings from the implementation, in consecutive years, of a research-validated multiple-choice question sequence [referred to in this study as a Clicker Question Sequence (CQS)] on quantum measurement as it applies to two-state quantum systems. This study was conducted in an advanced undergraduate quantum mechanics course, in both online and in-person learning environments across three years. Student learning was assessed after traditional lecture-based instruction in relevant concepts, and their performance was compared with that on a similar assessment given after engaging with the CQS. We analyze, compare, and discuss the trends observed in the three implementations., Comment: 30 pages, 3 figures

Published
2024
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7. Challenges in addressing student difficulties with time-development of two-state quantum systems using a multiple-choice question sequence in virtual and in-person classes

Author

Hu, Peter, Li, Yangqiuting, and Singh, Chandralekha

Subjects
Physics - Physics Education
Abstract

Research-validated clicker questions as instructional tools for formative assessment are relatively easy to implement and can provide effective scaffolding when developed and implemented in a sequence. We present findings from the implementation of a research-validated clicker question sequence (CQS) on student understanding of the time-development of two-state quantum systems. This study was conducted in an advanced undergraduate quantum mechanics course for two consecutive years in virtual and in-person classes. The effectiveness of the CQS discussed here in both modes of instruction was determined by evaluating students' performance after traditional lecture-based instruction and comparing it to their performance after engaging with the CQS., Comment: 18 pages, 1 figure

Published
2024
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8. Challenges in addressing student difficulties with basics and change of basis for two-state quantum systems using a multiple-choice question sequence in online and in-person classes

Author

Hu, Peter, Li, Yangqiuting, and Singh, Chandralekha

Subjects
Physics - Physics Education
Abstract

Research-validated multiple-choice questions comprise an easy-to-implement instructional tool for scaffolding student learning and providing formative assessment of students' knowledge. We present findings from the implementation of a research-validated multiple-choice question sequence on the basics of two-state quantum systems, including inner products, outer products, translation between Dirac notation and matrix representation in a particular basis, and change of basis. This study was conducted in an advanced undergraduate quantum mechanics course, in both online and in-person learning environments, across three years. For each cohort, students had their learning assessed after traditional lecture-based instruction in relevant concepts before engaging with the multiple-choice question sequence. Their performance was evaluated again afterwards with a similar assessment and compared to their earlier performance. We analyze, compare, and discuss the trends observed in the three implementations., Comment: 25 pages, 0 figures; added references

Published
2024
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13. Directed Use of the Internet for Health Information by Patients With Chronic Kidney Disease: Prospective Cohort Study

Author

Diamantidis, Clarissa Jonas, Fink, Wanda, Yang, Shiming, Zuckerman, Marni R, Ginsberg, Jennifer, Hu, Peter, Xiao, Yan, and Fink, Jeffrey C

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundHealth information technology has become common in the care of patients with chronic diseases; however, there are few such applications employed in kidney disease. ObjectiveThe aim of the study was to evaluate the use of a website providing disease-specific safety information by patients with predialysis chronic kidney disease. MethodsAs part of the Safe Kidney Care (SKC) study, an educational website was designed to provide information on safety concerns in chronic kidney disease. Phase I study participants were provided a medical alert accessory with a unique ID number, the Safe Kidney Care website, and an in-person tutorial on the use of the Internet and accessing the SKC website at baseline. Participants were asked to visit the website and enter their unique ID as frequently as they desired over the next 365 days or until their annual follow-up visit, whichever occurred first. Participants’ visits and dwell times on specific safety modules were tracked using embedded webpage PHP scripts linked to a MySQL database, enabling the collection of website usage statistics. ResultsOf 108 Phase I participants, 28.7% (31/108) visited the website from 1-6 times during the observation period (median follow-up 365 days). Median access time was 7 minutes per visit (range

Published
2013
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19. Preliminary Findings: Application of Maintenance Instructions Displayed in Augmented Reality

Author

Key, Kylie, Ma, Maggie, Towne, Chris, Choi, Inchul, Hu, Peter T., Franzman, Steven C., Aguilar, David R., Schroeder, David J., Avers, Katrina, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Jessie Y. C., editor, and Fragomeni, Gino, editor

Published
2022
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22. Effects of metformin and statins on outcomes in men with castration-resistant metastatic prostate cancer: Secondary analysis of COU-AA-301 and COU-AA-302

Author

Wilson, Brooke E., Armstrong, Andrew J., de Bono, Johann, Sternberg, Cora N., Ryan, Charles J., Scher, Howard I., Smith, Matthew R., Rathkopf, Dana, Logothetis, Christopher J., Chi, Kim N., Jones, Robert J., Saad, Fred, De Porre, Peter, Tran, NamPhuong, Hu, Peter, Gillessen, Silke, Carles, Joan, Fizazi, Karim, and Joshua, Anthony M.

Published
2022
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23. Machine Learning Approaches to Prognostication in Traumatic Brain Injury.

Author

Badjatia, Neeraj, Podell, Jamie, Felix, Ryan B., Chen, Lujie Karen, Dalton, Kenneth, Wang, Tina I., Yang, Shiming, and Hu, Peter

Abstract

Purpose of Review: This review investigates the use of machine learning (ML) in prognosticating outcomes for traumatic brain injury (TBI). It underscores the benefits of ML models in processing and integrating complex, multimodal data—including clinical, imaging, and physiological inputs—to identify intricate non-linear relationships that traditional methods might overlook. Recent Findings: ML algorithms of clinical features, neuroimaging, and metrics from the autonomic nervous system enhance the early detection of clinical deterioration and improve outcome prediction. Challenges persist, including issues of data variability, model interpretability, and overfitting. However, advancements in model standardization and validation are key to enhancing their clinical applicability. Summary: ML-based, multimodal approaches offer transformative potential for personalized treatment planning and patient management. Future directions include integrating digital twins and real-time continuous data analysis, reinforcing the idea that comprehensive data amalgamation is essential for precise, adaptive prognostication and decision-making in neurocritical care, ultimately leading to better patient outcomes. [ABSTRACT FROM AUTHOR]

Published
2025
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24. Retrospective study of incidence/prevalence of pigmentary maculopathy and retinopathy in patients receiving pentosan polysulfate sodium.

Author

Yuan, Zhong, Vaughan, Subusola, Jeffcoat, Carolyn, Hu, Peter, Yuson, Ritchie, Fife, Daniel, and Borkar, Durga

Subjects
INTERSTITIAL cystitis, VISUAL acuity, MACULAR degeneration, DATABASES, COHORT analysis
Abstract

Purpose: To evaluate prevalence and incidence rates of pigmentary maculopathy and retinopathy (PM/PR), and visual acuity (VA) changes in patients exposed to pentosan polysulfate sodium (PPS) and in patients with interstitial cystitis (IC) not exposed to PPS. Methods: This is a retrospective cohort study (January 2015–March 2021) which included adult de-identified patients from the American Academy of Ophthalmology IRIS® Registry (Intelligent Research in Sight) and Komodo Health database. Three patient cohorts were identified: two PPS-exposed patient cohorts, and Non-PPS-exposed IC patient cohort. Key study outcomes included PM/PR/Any (defined based on prior literature regardless of PPS exposure) and PM/PR/PPS (further defined by an algorithm that was based on clinical notes and other protocol-prespecified criteria in PPS-exposed patients), and VA changes in each respective cohort. Results: Prevalence of PM/PR/Any was relatively common in patients prior to PPS exposure (4.16%–8.43%). Incidence rate of PM/PR/PPS was uncommon in both PPS-exposed cohorts (0.13–0.15 per 100 person-years). Crude incidence rates of PM/PR/Any (based on ITT analysis) varied slightly across 3 study cohorts (2.13–2.81 and 2.38 per 100-person-years for PPS-exposed cohorts and Non-PPS-exposed IC cohort, respectively). Across all 3 study cohorts, patients with PM/PR/Any appeared to have approximately 2-fold higher proportion of 3 lines of VA worsening than those without PM/PR/Any. Conclusion: Prevalence of PM/PR was common in patients prior to PPS exposure. Incidence of PM/PR/PPS that may be associated with PPS exposure was relatively uncommon. Crude incidence rates of PM/PR appeared similar across all patient cohorts regardless of PPS exposure. [ABSTRACT FROM AUTHOR]

Published
2025
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25. Closing the gaps in the access to quality-assured medicines for global health: The case for oxytocin for postpartum haemorrhage.

Author

Lee, CC, Gwaza, Luther, Rombouts, Karin, Hu, Peter, Kuwana, Rutendo, Remmerie, Bart, Ejekam, Chioma, Okunade, Kehinde, and Lambert, Pete

Subjects
LOW-income countries, POSTPARTUM hemorrhage, OXYTOCIN, MIDDLE-income countries, HIGH-income countries
Abstract

Introduction: Access to quality-assured medicines remains unequal between high-income and low-income countries. To bridge this gap, product development and supply in low- and middle-income countries (LMICs) should follow World Health Organization (WHO)'s policies and recommendations whilst aligning with international standards. Areas covered: We reviewed two cases on oxytocin access for postpartum hemorrhage (PPH), a condition that disproportionately affects mothers in low-income countries. The first case examines the challenges in ensuring quality-assured oxytocin injections in LMICs. International technical guidelines allow different storage conditions for oxytocin, which can cause confusion in countries with weak regulatory oversight. WHO and partners recommend a common storage and management of oxytocin to resolve this issue. The second case explores the design of clinical studies for inhaled oxytocin, a promising candidate for PPH aiming for rapid registration and inclusion in WHO's therapeutic recommendations. Aligning scientific, regulatory, and WHO policy requirements early in the development process can expedite access to new effective medicines in LMICs, and we described the potential clinical challenges in meeting this. Expert opinion: Robust partnerships between stakeholders, to streamline medicine development and regulatory approval, are essential to close access gaps and ultimately prevent unnecessary deaths due to PPH in LMICs. [ABSTRACT FROM AUTHOR]

Published
2025
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28. Hierarchical One-Class Detection for Hyperspectral Image Classification With Background

Author

Chang, Chein-I, Liang, Chia-Chen, Chung, Pau-Choo, and Hu, Peter Fuming

Abstract

Hyperspectral image classification (HSIC) has received considerable interest in recent years where most techniques are developed to classify images with background (BKG) removed by ground truth (GT). Unfortunately, in real scenarios, obtaining complete BKG knowledge is generally infeasible. Accordingly, HSIC performed with no BKG (HSIC-NB) is not realistic. Most importantly, many techniques claim to work well for HSIC-NB but perform poorly with BKG included. This article investigates issues arising from BKG in HSIC and further presents a new approach to HSIC with BKG (HSIC-B), called one class detection (OCD), which is based on the well-known hyperspectral subpixel detection technique, constrained energy minimization (CEM). In order for OCD to perform multiclass classification, OCD is further extended to hierarchical OCD (HOC) which is particularly designed to classify multiple classes in a hierarchical tree where each layer uses an iterative kernel CEM (IKCEM) or an iterative kernel target-constrained interference-minimized filter (IKTCIMF) to detect one class at a time for classification. Since M classes are classified by OCD in ${M} -1$ layers in a hierarchical tree, a new concept of class classification priority (CCP) derived from CEM is specifically designed to rank all the classes along the tree in a prioritized order according to their CCP scores. The experimental results demonstrate that hierarchical OCD (HOCD) works well and performs significantly better than many existing HSIC-NB methods at the expense of slightly reduced classification accuracy compared to HSIC-N methods.

Published
2025
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29. COMPARISON OF CONTINUOUS VITAL SIGNS DATA ANALYSIS VERSUSVENOUS LACTATE FOR THE PREDICTION OF LIFESAVING INTERVENTIONS IN PATIENTS WITH TRAUMATIC SHOCK

Author

Yang, Shiming, Hu, Peter, Teeter, William, Floccare, Douglas J., Hu, Howard, and Galvagno, Samuel M.

Abstract

Introduction:The prehospital environment is fraught with operational constraints, making it difficult to assess the need for resources such as lifesaving interventions (LSI) for adults with traumatic injuries. While invasive methods such as lactate have been found to be highly predictive for estimating injury severity and resource requirements, noninvasive methods, to include continuous vital signs (VS), have the potential to provide prognostic information that can be quickly acquired, interpreted, and incorporated into decision making. In this work, we hypothesized that an analysis of continuous VSwould have predictive capacity comparable to lactate and other laboratory tests for the prediction of injury severity, need for LSIs and intensive care unit admission. Methods:In this preplanned secondary analysis of 300 prospectively enrolled patients, venous blood samples were collected in the prehospital environment aboard a helicopter and analyzed with a portable lab device. Patients were transported to the primary adult resource center for trauma in the state of Maryland. Continuous VSwere simultaneously collected. Descriptive statistics were used to describe the cohort and predictive models were constructed using a regularized gradient boosting framework with 10-fold cross-validation with additional analyses using Shapley additive explanations (SHAP). Results:Complete VSand laboratory data from 166 patients were available for analysis. The continuous VSmodels had better performance for prediction of receiving LSIs and intensive care unit length of stay compared to single (initial) VSmeasurements. The continuous VSmodels had comparable performance to models using only laboratory tests in predicting discharge within 24 h (continuous VSmodel: area under the receiver operating curve [AUROC] 0.71; 95% CI, 0.68–0.75 vs.lactate model: AUROC, 0.65; 95% CI, 0.68; 95% CI, 0.66–0.71). The model using all laboratory data yielded the highest sensitivity and sensitivity (AUROC, 0.77; 95% CI, 0.74–0.81). Discussion:The results from this study suggest that continuous VSobtained from autonomous monitors in an aeromedical environment may be helpful for predicting LSIs and the critical care requirements for traumatically injured adults. The collection and use of noninvasively obtained physiological data during the early stages of prehospital care may be useful for in developing user-friendly early warning systems for identifying potentially unstable trauma patients.

Published
2025
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31. Use of virtual visits for the care of the arrhythmia patient

Author

Hu, Peter T, Hilow, Henry, Patel, Divyang, Eppich, Megan, Cantillon, Daniel, Tchou, Patrick, Bhargava, Mandeep, Kanj, Mohamed, Baranowski, Bryan, Hussein, Ayman, Callahan, Thomas, Saliba, Walid, Dresing, Thomas, Wilkoff, Bruce L., Rasmussen, Peter A., Wazni, Oussama, and Tarakji, Khaldoun G.

Published
2020
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35. Highly synchronized cortical circuit dynamics mediate spontaneous pain in mice

Author

Ding, Weihua, Fischer, Lukas, Chen, Qian, Li, Ziyi, Yang, Liuyue, You, Zerong, Hu, Kun, Wu, Xinbo, Zhou, Xue, Chao, Wei, Hu, Peter, Dagnew, Tewodros Mulugeta, Dubreuil, Daniel M., Wang, Shiyu, Xia, Suyun, Bao, Caroline, Zhu, Shengmei, Chen, Lucy, Wang, Changning, Wainger, Brian, Jin, Peng, Mao, Jianren, Feng, Guoping, Harnet, Mark T., and Shen, Shiqian

Subjects
Physiological aspects, Development and progression, Health aspects, Neural oscillations -- Health aspects, Neural circuitry -- Health aspects, Somatosensory cortex -- Physiological aspects, Facial pain -- Development and progression, Orofacial pain -- Development and progression
Abstract

Introduction Although the functions of cortical circuits vary dramatically between brain regions and species, general principles have been found that constrain neural dynamics to stable activity regimes. For example, sleep, [...], Cortical neural dynamics mediate information processing for the cerebral cortex, which is implicated in fundamental biological processes such as vision and olfaction, in addition to neurological and psychiatric diseases. Spontaneous pain is a key feature of human neuropathic pain. Whether spontaneous pain pushes the cortical network into an aberrant state and, if so, whether it can be brought back to a "normal" operating range to ameliorate pain are unknown. Using a clinically relevant mouse model of neuropathic pain with spontaneous pain-like behavior, we report that orofacial spontaneous pain activated a specific area within the primary somatosensory cortex (S1), displaying synchronized neural dynamics revealed by intravital two-photon calcium imaging. This synchronization was underpinned by local GABAergic interneuron hypoactivity. Pain-induced cortical synchronization could be attenuated by manipulating local S1 networks or clinically effective pain therapies. Specifically, both chemogenetic inhibition of pain-related c-Fos-expressing neurons and selective activation of GABAergic interneurons significantly attenuated S1 synchronization. Clinically effective pain therapies including carbamazepine and nerve root decompression could also dampen S1 synchronization. More important, restoring a "normal" range of neural dynamics through attenuation of pain-induced S1 synchronization alleviated pain-like behavior. These results suggest that spontaneous pain pushed the S1 regional network into a synchronized state, whereas reversal of this synchronization alleviated pain.

Published
2023
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36. Treatment Pattern and Outcomes in Newly Diagnosed Multiple Myeloma Patients Who Did Not Receive Autologous Stem Cell Transplantation: A Real-World Observational Study: Treatment pattern and outcomes in patients with multiple myeloma

Author

He, Jianming, Schmerold, Luke, Van Rampelbergh, Rian, Qiu, Lugui, Potluri, Ravi, Dasgupta, Anandaroop, Li, Lin, Li, Yunan, Hu, Peter, Nemat, Sepideh, Smugar, Steven S., Zeltzer, Paul, Appiani, Carlos, Li, Qing, Mehra, Maneesha, and Richarz, Ute

Published
2021
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37. Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Outcomes and Endpoints

Author

Bodien, Y, Larovere, K, Kondziella, D, Taran, S, Estraneo, A, Shutter, L, Null, N, Aiyagari, V, Akbari, Y, Al-Mufti, F, Alexander, S, Alexandrov, A, Alkhachroum, A, Amiri, M, Appavu, B, Gebre, M, Bader, M, Badjiata, N, Balu, R, Barra, M, Beekman, R, Beghi, E, Bell, K, Beqiri, E, Berlin, T, Bleck, T, Boerwinkle, V, Boly, M, Bonnel, A, Brown, E, Caceres, E, Carroll, E, Cediel, E, Chou, S, Citerio, G, Claassen, J, Condie, C, Cosmas, K, Creutzfeldt, C, Dangayach, N, Degeorgia, M, Der-Nigoghossian, C, Desai, M, Diringer, M, Dullaway, J, Edlow, B, Ercole, A, Falcone, G, Farrokh, S, Ferioli, S, Fernandez-Espejo, D, Fink, E, Fins, J, Foreman, B, Frontera, J, Ganesan, R, Ghavam, A, Giacino, J, Gibbons, C, Gilmore, E, Gosseries, O, Green, T, Greer, D, Guanci, M, Hahn, C, Hakimi, R, Hammond, F, Hanley, D, Hartings, J, Hassan, A, Hemphill, C, Hinson, H, Hirsch, K, Hocker, S, Hu, P, Hu, X, Human, T, Hwang, D, Illes, J, Jaffa, M, James, M, Janas, A, Jones, M, Keller, E, Keogh, M, Kim, J, Kim, K, Kirsch, H, Kirschen, M, Ko, N, Kreitzer, N, Kromm, J, Kumar, A, Kurtz, P, Laureys, S, Lawson, T, Lejeune, N, Lewis, A, Liang, J, Ling, G, Livesay, S, Luppi, A, Madden, L, Maddux, C, Mahanes, D, Mainali, S, Maldonado, N, Ribeiro, R, Massimini, M, Mayer, S, Mccredie, V, Mcnett, M, Mejia-Mantilla, J, Menon, D, Meyfroidt, G, Mijangos, J, Moberg, D, Moheet, A, Molteni, E, Monti, M, Morrison, C, Muehlschlegel, S, Murtaugh, B, Naccache, L, Nagayama, M, Nairon, E, Natarajan, G, Newcombe, V, Nielsen, N, Niznick, N, Noronha-Falcão, F, Nyquist, P, Olson, D, Othman, M, Owen, A, Padayachy, L, Park, S, Pergakis, M, Polizzotto, L, Pouratian, N, Spivack, M, Prisco, L, Provencio, J, Puybasset, L, Rao, C, Rasmussen, L, Rass, V, Reznik, M, Richardson, R, Shinotsuka, C, Robba, C, Robertson, C, Rohaut, B, Rolston, J, Rosanova, M, Rosenthal, E, Russell, M, Silva, G, Sanz, L, Sarasso, S, Sarwal, A, Schiff, N, Schnakers, C, Seder, D, Shah, V, Shapiro-Rosen, A, Shapshak, A, Sharma, K, Sharshar, T, Sitt, J, Slomine, B, Smielewski, P, Smith, W, Stamatakis, E, Steinberg, A, Stevens, R, Suarez, J, Sussman, B, Thibaut, A, Threlkeld, Z, Tinti, L, Toker, D, Torbey, M, Trevick, S, Turgeon, A, Udy, A, Varelas, P, Vespa, P, Videtta, W, Voss, H, Vox, F, Wagner, A, Wainwright, M, Whyte, J, Witherspoon, B, Yakhind, A, Zafonte, R, Zahuranec, D, Zammit, C, Zhang, B, Ziai, W, Zimmerman, L, Zink, E, Bodien, Yelena G., LaRovere, Kerri, Kondziella, Daniel, Taran, Shaurya, Estraneo, Anna, Shutter, Lori, null, null, Aiyagari, Venkatesh, Akbari, Yama, Al-Mufti, Fawaz, Alexander, Sheila, Alexandrov, Anne, Alkhachroum, Ayham, Amiri, Moshagan, Appavu, Brian, Gebre, Meron Awraris, Bader, Mary Kay, Badjiata, Neeraj, Balu, Ram, Barra, Megan, Beekman, Rachel, Beghi, Ettore, Bell, Kathleen, Beqiri, Erta, Berlin, Tracey, Bleck, Thomas, Bodien, Yelena, Boerwinkle, Varina, Boly, Melanie, Bonnel, Alexandra, Brown, Emery, Caceres, Eder, Carroll, Elizabeth, Cediel, Emilio, Chou, Sherry, Citerio, Giuseppe, Claassen, Jan, Condie, Chad, Cosmas, Katie, Creutzfeldt, Claire, Dangayach, Neha, DeGeorgia, Michael, Der-Nigoghossian, Caroline, Desai, Masoom, Diringer, Michael, Dullaway, James, Edlow, Brian, Ercole, Ari, Falcone, Guido, Farrokh, Salia, Ferioli, Simona, Fernandez-Espejo, Davinia, Fink, Ericka, Fins, Joseph, Foreman, Brandon, Frontera, Jennifer, Ganesan, Rishi, Ghavam, Ahmeneh, Giacino, Joseph, Gibbons, Christie, Gilmore, Emily, Gosseries, Olivia, Green, Theresa, Greer, David, Guanci, Mary, Hahn, Cecil, Hakimi, Ryan, Hammond, Flora, Hanley, Daniel, Hartings, Jed, Hassan, Ahmed, Hemphill, Claude, Hinson, H. E., Hirsch, Karen, Hocker, Sarah, Hu, Peter, Hu, Xiao, Human, Theresa, Hwang, David, Illes, Judy, Jaffa, Matthew, James, Michael L., Janas, Anna, Jones, Morgan, Keller, Emanuela, Keogh, Maggie, Kim, Jenn, Kim, Keri, Kirsch, Hannah, Kirschen, Matt, Ko, Nerissa, Kreitzer, Natalie, Kromm, Julie, Kumar, Abhay, Kurtz, Pedro, Laureys, Steven, Lawson, Thomas, Lejeune, Nicolas, Lewis, Ariane, Liang, John, Ling, Geoffrey, Livesay, Sarah, Luppi, Andrea, Madden, Lori, Maddux, Craig, Mahanes, Dea, Mainali, Shraddha, Maldonado, Nelson, Ribeiro, Rennan Martins, Massimini, Marcello, Mayer, Stephan, McCredie, Victoria, McNett, Molly, Mejia-Mantilla, Jorge, Menon, David, Meyfroidt, Geert, Mijangos, Julio, Moberg, Dick, Moheet, Asma, Molteni, Erika, Monti, Martin, Morrison, Chris, Muehlschlegel, Susanne, Murtaugh, Brooke, Naccache, Lionel, Nagayama, Masao, Nairon, Emerson, Natarajan, Girija, Newcombe, Virginia, Nielsen, Niklas, Niznick, Naomi, Noronha-Falcão, Filipa, Nyquist, Paul, Olson, DaiWai, Othman, Marwan, Owen, Adrian, Padayachy, Llewellyn, Park, Soojin, Pergakis, Melissa, Polizzotto, Len, Pouratian, Nader, Spivack, Marilyn Price, Prisco, Lara, Provencio, Javier, Puybasset, Louis, Rao, Chethan, Rasmussen, Lindsay, Rass, Verena, Reznik, Michael, Richardson, Risa, Shinotsuka, Cassia Righy, Robba, Chiara, Robertson, Courtney, Rohaut, Benjamin, Rolston, John, Rosanova, Mario, Rosenthal, Eric, Russell, Mary Beth, Silva, Gisele Sampaio, Sanz, Leandro, Sarasso, Simone, Sarwal, Aarti, Schiff, Nicolas, Schnakers, Caroline, Seder, David, Shah, Vishank, Shapiro-Rosen, Amy, Shapshak, Angela, Sharma, Kartavya, Sharshar, Tarek, Sitt, Jacobo, Slomine, Beth, Smielewski, Peter, Smith, Wade, Stamatakis, Emmanuel, Steinberg, Alexis, Stevens, Robert, Suarez, Jose, Sussman, Bethany, Thibaut, Aurore, Threlkeld, Zachary, Tinti, Lorenzo, Toker, Daniel, Torbey, Michel, Trevick, Stephen, Turgeon, Alexis, Udy, Andrew, Varelas, Panos, Vespa, Paul, Videtta, Walter, Voss, Henning, Vox, Ford, Wagner, Amy, Wainwright, Mark, Whyte, John, Witherspoon, Briana, Yakhind, Aleksandra, Zafonte, Ross, Zahuranec, Darin, Zammit, Chris, Zhang, Bei, Ziai, Wendy, Zimmerman, Lara, Zink, Elizabeth, Bodien, Y, Larovere, K, Kondziella, D, Taran, S, Estraneo, A, Shutter, L, Null, N, Aiyagari, V, Akbari, Y, Al-Mufti, F, Alexander, S, Alexandrov, A, Alkhachroum, A, Amiri, M, Appavu, B, Gebre, M, Bader, M, Badjiata, N, Balu, R, Barra, M, Beekman, R, Beghi, E, Bell, K, Beqiri, E, Berlin, T, Bleck, T, Boerwinkle, V, Boly, M, Bonnel, A, Brown, E, Caceres, E, Carroll, E, Cediel, E, Chou, S, Citerio, G, Claassen, J, Condie, C, Cosmas, K, Creutzfeldt, C, Dangayach, N, Degeorgia, M, Der-Nigoghossian, C, Desai, M, Diringer, M, Dullaway, J, Edlow, B, Ercole, A, Falcone, G, Farrokh, S, Ferioli, S, Fernandez-Espejo, D, Fink, E, Fins, J, Foreman, B, Frontera, J, Ganesan, R, Ghavam, A, Giacino, J, Gibbons, C, Gilmore, E, Gosseries, O, Green, T, Greer, D, Guanci, M, Hahn, C, Hakimi, R, Hammond, F, Hanley, D, Hartings, J, Hassan, A, Hemphill, C, Hinson, H, Hirsch, K, Hocker, S, Hu, P, Hu, X, Human, T, Hwang, D, Illes, J, Jaffa, M, James, M, Janas, A, Jones, M, Keller, E, Keogh, M, Kim, J, Kim, K, Kirsch, H, Kirschen, M, Ko, N, Kreitzer, N, Kromm, J, Kumar, A, Kurtz, P, Laureys, S, Lawson, T, Lejeune, N, Lewis, A, Liang, J, Ling, G, Livesay, S, Luppi, A, Madden, L, Maddux, C, Mahanes, D, Mainali, S, Maldonado, N, Ribeiro, R, Massimini, M, Mayer, S, Mccredie, V, Mcnett, M, Mejia-Mantilla, J, Menon, D, Meyfroidt, G, Mijangos, J, Moberg, D, Moheet, A, Molteni, E, Monti, M, Morrison, C, Muehlschlegel, S, Murtaugh, B, Naccache, L, Nagayama, M, Nairon, E, Natarajan, G, Newcombe, V, Nielsen, N, Niznick, N, Noronha-Falcão, F, Nyquist, P, Olson, D, Othman, M, Owen, A, Padayachy, L, Park, S, Pergakis, M, Polizzotto, L, Pouratian, N, Spivack, M, Prisco, L, Provencio, J, Puybasset, L, Rao, C, Rasmussen, L, Rass, V, Reznik, M, Richardson, R, Shinotsuka, C, Robba, C, Robertson, C, Rohaut, B, Rolston, J, Rosanova, M, Rosenthal, E, Russell, M, Silva, G, Sanz, L, Sarasso, S, Sarwal, A, Schiff, N, Schnakers, C, Seder, D, Shah, V, Shapiro-Rosen, A, Shapshak, A, Sharma, K, Sharshar, T, Sitt, J, Slomine, B, Smielewski, P, Smith, W, Stamatakis, E, Steinberg, A, Stevens, R, Suarez, J, Sussman, B, Thibaut, A, Threlkeld, Z, Tinti, L, Toker, D, Torbey, M, Trevick, S, Turgeon, A, Udy, A, Varelas, P, Vespa, P, Videtta, W, Voss, H, Vox, F, Wagner, A, Wainwright, M, Whyte, J, Witherspoon, B, Yakhind, A, Zafonte, R, Zahuranec, D, Zammit, C, Zhang, B, Ziai, W, Zimmerman, L, Zink, E, Bodien, Yelena G., LaRovere, Kerri, Kondziella, Daniel, Taran, Shaurya, Estraneo, Anna, Shutter, Lori, null, null, Aiyagari, Venkatesh, Akbari, Yama, Al-Mufti, Fawaz, Alexander, Sheila, Alexandrov, Anne, Alkhachroum, Ayham, Amiri, Moshagan, Appavu, Brian, Gebre, Meron Awraris, Bader, Mary Kay, Badjiata, Neeraj, Balu, Ram, Barra, Megan, Beekman, Rachel, Beghi, Ettore, Bell, Kathleen, Beqiri, Erta, Berlin, Tracey, Bleck, Thomas, Bodien, Yelena, Boerwinkle, Varina, Boly, Melanie, Bonnel, Alexandra, Brown, Emery, Caceres, Eder, Carroll, Elizabeth, Cediel, Emilio, Chou, Sherry, Citerio, Giuseppe, Claassen, Jan, Condie, Chad, Cosmas, Katie, Creutzfeldt, Claire, Dangayach, Neha, DeGeorgia, Michael, Der-Nigoghossian, Caroline, Desai, Masoom, Diringer, Michael, Dullaway, James, Edlow, Brian, Ercole, Ari, Falcone, Guido, Farrokh, Salia, Ferioli, Simona, Fernandez-Espejo, Davinia, Fink, Ericka, Fins, Joseph, Foreman, Brandon, Frontera, Jennifer, Ganesan, Rishi, Ghavam, Ahmeneh, Giacino, Joseph, Gibbons, Christie, Gilmore, Emily, Gosseries, Olivia, Green, Theresa, Greer, David, Guanci, Mary, Hahn, Cecil, Hakimi, Ryan, Hammond, Flora, Hanley, Daniel, Hartings, Jed, Hassan, Ahmed, Hemphill, Claude, Hinson, H. E., Hirsch, Karen, Hocker, Sarah, Hu, Peter, Hu, Xiao, Human, Theresa, Hwang, David, Illes, Judy, Jaffa, Matthew, James, Michael L., Janas, Anna, Jones, Morgan, Keller, Emanuela, Keogh, Maggie, Kim, Jenn, Kim, Keri, Kirsch, Hannah, Kirschen, Matt, Ko, Nerissa, Kreitzer, Natalie, Kromm, Julie, Kumar, Abhay, Kurtz, Pedro, Laureys, Steven, Lawson, Thomas, Lejeune, Nicolas, Lewis, Ariane, Liang, John, Ling, Geoffrey, Livesay, Sarah, Luppi, Andrea, Madden, Lori, Maddux, Craig, Mahanes, Dea, Mainali, Shraddha, Maldonado, Nelson, Ribeiro, Rennan Martins, Massimini, Marcello, Mayer, Stephan, McCredie, Victoria, McNett, Molly, Mejia-Mantilla, Jorge, Menon, David, Meyfroidt, Geert, Mijangos, Julio, Moberg, Dick, Moheet, Asma, Molteni, Erika, Monti, Martin, Morrison, Chris, Muehlschlegel, Susanne, Murtaugh, Brooke, Naccache, Lionel, Nagayama, Masao, Nairon, Emerson, Natarajan, Girija, Newcombe, Virginia, Nielsen, Niklas, Niznick, Naomi, Noronha-Falcão, Filipa, Nyquist, Paul, Olson, DaiWai, Othman, Marwan, Owen, Adrian, Padayachy, Llewellyn, Park, Soojin, Pergakis, Melissa, Polizzotto, Len, Pouratian, Nader, Spivack, Marilyn Price, Prisco, Lara, Provencio, Javier, Puybasset, Louis, Rao, Chethan, Rasmussen, Lindsay, Rass, Verena, Reznik, Michael, Richardson, Risa, Shinotsuka, Cassia Righy, Robba, Chiara, Robertson, Courtney, Rohaut, Benjamin, Rolston, John, Rosanova, Mario, Rosenthal, Eric, Russell, Mary Beth, Silva, Gisele Sampaio, Sanz, Leandro, Sarasso, Simone, Sarwal, Aarti, Schiff, Nicolas, Schnakers, Caroline, Seder, David, Shah, Vishank, Shapiro-Rosen, Amy, Shapshak, Angela, Sharma, Kartavya, Sharshar, Tarek, Sitt, Jacobo, Slomine, Beth, Smielewski, Peter, Smith, Wade, Stamatakis, Emmanuel, Steinberg, Alexis, Stevens, Robert, Suarez, Jose, Sussman, Bethany, Thibaut, Aurore, Threlkeld, Zachary, Tinti, Lorenzo, Toker, Daniel, Torbey, Michel, Trevick, Stephen, Turgeon, Alexis, Udy, Andrew, Varelas, Panos, Vespa, Paul, Videtta, Walter, Voss, Henning, Vox, Ford, Wagner, Amy, Wainwright, Mark, Whyte, John, Witherspoon, Briana, Yakhind, Aleksandra, Zafonte, Ross, Zahuranec, Darin, Zammit, Chris, Zhang, Bei, Ziai, Wendy, Zimmerman, Lara, and Zink, Elizabeth

Abstract

Background: Clinical management of persons with disorders of consciousness (DoC) is dedicated largely to optimizing recovery. However, selecting a measure to evaluate the extent of recovery is challenging because few measures are designed to precisely assess the full range of potential outcomes, from prolonged DoC to return of preinjury functioning. Measures that are designed specifically to assess persons with DoC are often performance-based and only validated for in-person use. Moreover, there are no published recommendations addressing which outcome measures should be used to evaluate DoC recovery. The resulting inconsistency in the measures selected by individual investigators to assess outcome prevents comparison of results across DoC studies. The National Institute of Neurological Disorders and Stroke (NINDS) common data elements (CDEs) is an amalgamation of standardized variables and tools that are recommended for use in studies of neurologic diseases and injuries. The Neurocritical Care Society Curing Coma Campaign launched an initiative to develop CDEs specifically for DoC and invited our group to recommend CDE outcomes and endpoints for persons with DoCs. Methods: The Curing Coma Campaign Outcomes and Endpoints CDE Workgroup, consisting of experts in adult and pediatric neurocritical care, neurology, and neuroscience, used a previously established five-step process to identify and select candidate CDEs: (1) review of existing NINDS CDEs, (2) nomination and systematic vetting of new CDEs, (3) CDE classification, (4) iterative review and approval of panel recommendations, and (5) development of case report forms. Results: Among hundreds of existing NINDS outcome and endpoint CDE measures, we identified 20 for adults and 18 for children that can be used to assess the full range of recovery from coma. We also proposed 14 new outcome and endpoint CDE measures for adults and 5 for children. Conclusions: The DoC outcome and endpoint CDEs are a starting point in t

Published
2024

38. Investigating and Improving Student Understanding of Quantum Mechanics Using Research-Validated Clicker Question Sequences and Tutorials

Author

Hu, Peter Tianyi and Hu, Peter Tianyi

Abstract

Quantum mechanics is notoriously challenging, and research has found that students struggle with many common difficulties when learning it. It is also proving to be a critical piece of many exciting fields that are all but assured to see great development and expansion in the coming years; the Second Quantum Revolution is upon us. Quantum information science and engineering is a rapidly unfolding field, requiring talent from many disciplines, that aims to leverage the potential of quantum systems for many practical applications. To prepare students for the opportunities afforded by these advances, a strong foundation in quantum mechanics is essential. The work that I present in this dissertation is focused on helping students achieve this understanding. By investigating the common difficulties that students have in key concepts related to quantum mechanics and quantum computing, a guiding framework can be established and followed to develop research-validated, active-engagement instructional tools. These tools include Clicker Question Sequences (CQSs) on (1) the basics of two-state quantum systems, and changing basis in two-state systems; (2) time-development of two-state systems; (3) quantum measurement of two-state systems, and (4) measurement uncertainty in two-state systems. In addition to these, I have developed and validated Quantum Interactive Learning Tutorials (QuILTs) consisting of guided-inquiry teaching-learning sequences for (1) the Bloch sphere and (2) the basics of quantum computing. In each case, cognitive task analysis from both expert and student perspectives was either carried out directly or built upon from the results of prior investigations. I discuss the results of implementations of these learning tools in authentic classroom environments, which involves both online and in-person administrations and multiple instructors. In each case, student performance after engaging with the learning tools increased noticeably, and dramatically for some di

Published
2024

39. Research considerations for prospective studies of patients with coma and disorders of consciousness

Author

Tinti, L, Lawson, T, Molteni, E, Kondziella, D, Rass, V, Sharshar, T, Bodien, Y, Giacino, J, Mayer, S, Amiri, M, Muehlschlegel, S, Venkatasubba Rao, C, Vespa, P, Menon, D, Citerio, G, Helbok, R, Mcnett, M, Agarwal, S, Aiyagari, V, Akbari, Y, Albertson, A, Alexander, S, Alexandrov, A, Alkhachroum, A, Al-Mufti, F, Appavu, B, Gebrewold, M, Ayounb, M, Badenes, R, Bader, M, Badjiata, N, Balu, R, Barlow, B, Barra, M, Beekman, R, Beghi, E, Beqiri, E, Berlin, T, Bilotta, F, Bleck, T, Boerwinkle, V, Boly, M, Bonnel, A, Brazzi, L, Brown, E, Bulic, S, Caceres, E, Caceres, A, Cafiero, T, Carroll, E, Cediel, E, Chou, S, Claassen, J, Condie, C, Conti, A, Cosmas, K, Costa, P, Creutzfeldt, C, Dangayach, N, Dauri, M, Debicki, D, Degeorgia, M, Der-Nigoghossian, C, Desai, M, Dhar, R, Diringer, M, Durr, E, Edlow, B, Ercole, A, Estraneo, A, Falcone, G, Farrokh, S, Ferguson, A, Fernandez-Espejo, D, Fink, E, Fins, J, Foreman, B, Franchi, F, Frontera, J, Ganesan, R, Gaspard, N, Ghavam, A, Gibbons, C, Gilmore, E, Glustein, C, Gosseries, O, Green, T, Greer, D, Guanci, M, Gupta, D, Hahn, C, Hakimi, R, Hammond, F, Hanley, D, Hartings, J, Hassan, A, Hemphill, C, Da Cunha, A, Hinson, H, Hirsch, K, Hocker, S, Hu, P, Hu, X, Human, T, Hwang, D, Illes, J, Jaffa, M, James, M, Janas, A, Johnson, S, Jones, M, Jox, R, Kalanuria, A, Keller, E, Kennedy, L, Kennelly, M, Keogh, M, Kim, J, Kim, K, Kirsch, H, Kirschen, M, Ko, N, Kreitzer, N, Kromm, J, Kumar, A, Kurtz, P, Laureys, S, Lejeune, N, Lewis, A, Liang, J, Ling, G, Livesay, S, Luppi, A, Macdonald, J, Maddux, C, Mahanes, D, Mainali, S, Maldonado, N, Ribeiro, R, Mascia, L, Massimini, M, Mathur, R, Mccredie, V, Mejia-Mantilla, J, Mendoza, M, Meyfroidt, G, Mijangos, J, Moberg, D, Moheet, A, Montalenti, E, Monti, M, Morrison, C, Munar, M, Murtaugh, B, Naccache, L, Nagayama, M, Nairon, E, Nakagawa, T, Naldi, A, Narenthiran, G, Natarajan, G, Nemetsky, E, Newcombe, V, Nielsen, N, Niznick, N, Noronha-Falcão, F, Nyquist, P, Olson, D, Othman, M, Owen, A, Padayachy, L, Pajoumand, M, Park, S, Pergakis, M, Perry, H, Polizzotto, L, Pouratian, N, Spivack, M, Prisco, L, Provencio, J, Puglises, F, Puybasset, L, Rao, C, Rasmussen, L, Rasulo, F, Ray, B, Ricci, Z, Richardson, R, Shinotsuka, C, Robba, C, Robertson, C, Rohaut, B, Rolston, J, Romagnoli, S, Rosanova, M, Rosenthal, E, Rowe, S, Rubin, M, Russell, M, Silva, G, Sanz, L, Sarasso, S, Sarwal, A, Schiff, N, Schnakers, C, Seder, D, Shah, V, Shapiro-Rosenbaubm, A, Shapshak, A, Sharma, K, Shutter, L, Sitt, J, Slomine, B, Smetana, K, Smielewski, P, Smith, W, Stamatakis, E, Steinberg, A, Stevens, R, Suarez, J, Sung, G, Sussman, B, Taran, S, Mazzeo, A, Thibaut, A, Thompson, D, Threlkeld, Z, Toker, D, Torbey, M, Tosto, J, Trevick, S, Tsaousi, G, Turgeon, A, Udy, A, Varelas, P, Videtta, W, Voss, H, Vox, F, Wagner, A, Wahlster, S, Wainwright, M, Whyte, J, Witherspoon, B, Yakhkind, A, Yeager, S, Young, M, Zafar, S, Zafonte, R, Zahuranec, D, Zammit, C, Zhang, B, Ziai, W, Zimmerman, L, Zink, E, Tinti, Lorenzo, Lawson, Thomas, Molteni, Erika, Kondziella, Daniel, Rass, Verena, Sharshar, Tarek, Bodien, Yelena G, Giacino, Joseph T, Mayer, Stephan A, Amiri, Moshgan, Muehlschlegel, Susanne, Venkatasubba Rao, Chethan P, Vespa, Paul M, Menon, David K, Citerio, Giuseppe, Helbok, Raimund, McNett, Molly, Agarwal, Sachin, Aiyagari, Venkatesh, Akbari, Yama, Albertson, Asher, Alexander, Sheila, Alexandrov, Anne, Alkhachroum, Ayham, Al-Mufti, Fawaz, Amiri, Moshagan, Appavu, Brian, Gebrewold, Meron Awraris, Ayounb, Marc, Badenes, Rafael, Bader, Mary Kay, Badjiata, Neeraj, Balu, Ram, Barlow, Brooke, Barra, Megan, Beekman, Rachel, Beghi, Ettore, Beqiri, Erta, Berlin, Tracey, Bilotta, Federico, Bleck, Thomas, Bodien, Yelena, Boerwinkle, Varina, Boly, Melanie, Bonnel, Alexandra, Brazzi, Luca, Brown, Emery, Bulic, Sebina, Caceres, Eder, Caceres, Adrian, Cafiero, Tullio, Carroll, Elizabeth, Cediel, Emilio G, Chou, Sherry, Claassen, Jan, Condie, Chad, Conti, Alfredo, Cosmas, Katie, Costa, Paolo, Creutzfeldt, Claire, Dangayach, Neha, Dauri, Mario, Debicki, Derek, DeGeorgia, Michael, Der-Nigoghossian, Caroline, Desai, Masoom, Dhar, Rajat, Diringer, Michael, Durr, Emily, Edlow, Brian, Ercole, Ari, Estraneo, Anna, Falcone, Guido, Farrokh, Salia, Ferguson, Adam, Fernandez-Espejo, Davinia, Fink, Ericka, Fins, Joseph, Foreman, Brandon, Franchi, Federico, Frontera, Jennifer, Ganesan, Rishi, Gaspard, Nicolas, Ghavam, Ahmeneh, Giacino, Joseph, Gibbons, Christie, Gilmore, Emily, Glustein, Chavie, Gosseries, Olivia, Green, Theresa, Greer, David, Guanci, Mary, Gupta, Deepak, Hahn, Cecil, Hakimi, Ryan, Hammond, Flora, Hanley, Daniel F, Hartings, Jed, Hassan, Ahmed, Hemphill, Claude, Da Cunha, Arthur Henrique Galvão Bruno, Hinson, Holly, Hirsch, Karen, Hocker, Sarah, Hu, Peter, Hu, Xiao, Human, Theresa, Hwang, David, Illes, Judy, Jaffa, Matthew, James, Michael L, Janas, Anna, Johnson, Susan, Jones, Morgan, Jox, Ralf J, Kalanuria, Atul, Keller, Emanuela, Kennedy, Lori, Kennelly, Megan, Keogh, Maggie, Kim, Jenn, Kim, Keri, Kirsch, Hannah, Kirschen, Matthew, Ko, Nerissa, Kreitzer, Natalie, Kromm, Julie, Kumar, Abhay, Kurtz, Pedro, Laureys, Steven, Lejeune, Nicolas, Lewis, Ariane, Liang, John, Ling, Geoffrey, Livesay, Sarah, Luppi, Andrea, MacDonald, Jennifer, Maddux, Craig, Mahanes, Dea, Mainali, Shraddha, Maldonado, Nelson, Ribeiro, Rennan Martins, Mascia, Luciana, Massimini, Marcello, Mathur, Rohan, Mayer, Stephan, McCredie, Victoria, Mejia-Mantilla, Jorge, Mendoza, Michael, Menon, David, Meyfroidt, Geert, Mijangos, Julio, Moberg, Dick, Moheet, Asma, Montalenti, Elisa, Monti, Martin, Morrison, Chris, Munar, Marina, Murtaugh, Brooke, Naccache, Lionel, Nagayama, Masao, Nairon, Emerson, Nakagawa, Thomas, Naldi, Andrea, Narenthiran, Ganesalingam, Natarajan, Girija, Nemetsky, Esther, Newcombe, Virginia, Nielsen, Niklas, Niznick, Naomi, Noronha-Falcão, Filipa, Nyquist, Paul, Olson, DaiWai, Othman, Marwan, Owen, Adrian, Padayachy, Llewellyn, Pajoumand, Mehrnaz, Park, Soojin, Pergakis, Melissa, Perry, Heidi, Polizzotto, Len, Pouratian, Nader, Spivack, Marilyn Price, Prisco, Lara, Provencio, Javier, Puglises, Francesco, Puybasset, Louis, Rao, Chethan, Rasmussen, Lindsay, Rasulo, Frank, Ray, Bappaditya, Ricci, Zaccaria, Richardson, Risa, Shinotsuka, Cassia Righy, Robba, Chiara, Robertson, Courtney, Rohaut, Benjamin, Rolston, John, Romagnoli, Stefano, Rosanova, Mario, Rosenthal, Eric, Rowe, Shaun, Rubin, Michael, Russell, Mary Beth, Silva, Gisele Sampaio, Sanz, Leandro, Sarasso, Simone, Sarwal, Aarti, Schiff, Nicolas, Schnakers, Caroline, Seder, David, Shah, Vishank Arun, Shapiro-Rosenbaubm, Amy, Shapshak, Angela, Sharma, Kartavya, Sharma, Kumar Ajay, Shutter, Lori, Sitt, Jacobo, Slomine, Beth, Smetana, Keaton, Smielewski, Peter, Smith, Wade, Stamatakis, Emmanuel, Steinberg, Alexis, Stevens, Robert, Suarez, Jose, Sung, Gene, Sussman, Bethany, Taran, Shaurya, Mazzeo, Anna Teresa, Thibaut, Aurore, Thompson, David, Threlkeld, Zachary, Toker, Daniel, Torbey, Michel, Tosto, Jenna, Trevick, Stephen, Tsaousi, Georgia, Turgeon, Alexis, Udy, Andrew, Varelas, Panos, Vespa, Paul, Videtta, Walter, Voss, Henning, Vox, Ford, Wagner, Amy, Wahlster, Sarah, Wainwright, Mark, Whyte, John, Witherspoon, Briana, Yakhkind, Aleksandra (Sasha), Yeager, Susan, Young, Michael, Zafar, Sahar, Zafonte, Ross, Zahuranec, Darin, Zammit, Chris, Zhang, Bei, Ziai, Wendy, Zimmerman, Lara, Zink, Elizabeth, Tinti, L, Lawson, T, Molteni, E, Kondziella, D, Rass, V, Sharshar, T, Bodien, Y, Giacino, J, Mayer, S, Amiri, M, Muehlschlegel, S, Venkatasubba Rao, C, Vespa, P, Menon, D, Citerio, G, Helbok, R, Mcnett, M, Agarwal, S, Aiyagari, V, Akbari, Y, Albertson, A, Alexander, S, Alexandrov, A, Alkhachroum, A, Al-Mufti, F, Appavu, B, Gebrewold, M, Ayounb, M, Badenes, R, Bader, M, Badjiata, N, Balu, R, Barlow, B, Barra, M, Beekman, R, Beghi, E, Beqiri, E, Berlin, T, Bilotta, F, Bleck, T, Boerwinkle, V, Boly, M, Bonnel, A, Brazzi, L, Brown, E, Bulic, S, Caceres, E, Caceres, A, Cafiero, T, Carroll, E, Cediel, E, Chou, S, Claassen, J, Condie, C, Conti, A, Cosmas, K, Costa, P, Creutzfeldt, C, Dangayach, N, Dauri, M, Debicki, D, Degeorgia, M, Der-Nigoghossian, C, Desai, M, Dhar, R, Diringer, M, Durr, E, Edlow, B, Ercole, A, Estraneo, A, Falcone, G, Farrokh, S, Ferguson, A, Fernandez-Espejo, D, Fink, E, Fins, J, Foreman, B, Franchi, F, Frontera, J, Ganesan, R, Gaspard, N, Ghavam, A, Gibbons, C, Gilmore, E, Glustein, C, Gosseries, O, Green, T, Greer, D, Guanci, M, Gupta, D, Hahn, C, Hakimi, R, Hammond, F, Hanley, D, Hartings, J, Hassan, A, Hemphill, C, Da Cunha, A, Hinson, H, Hirsch, K, Hocker, S, Hu, P, Hu, X, Human, T, Hwang, D, Illes, J, Jaffa, M, James, M, Janas, A, Johnson, S, Jones, M, Jox, R, Kalanuria, A, Keller, E, Kennedy, L, Kennelly, M, Keogh, M, Kim, J, Kim, K, Kirsch, H, Kirschen, M, Ko, N, Kreitzer, N, Kromm, J, Kumar, A, Kurtz, P, Laureys, S, Lejeune, N, Lewis, A, Liang, J, Ling, G, Livesay, S, Luppi, A, Macdonald, J, Maddux, C, Mahanes, D, Mainali, S, Maldonado, N, Ribeiro, R, Mascia, L, Massimini, M, Mathur, R, Mccredie, V, Mejia-Mantilla, J, Mendoza, M, Meyfroidt, G, Mijangos, J, Moberg, D, Moheet, A, Montalenti, E, Monti, M, Morrison, C, Munar, M, Murtaugh, B, Naccache, L, Nagayama, M, Nairon, E, Nakagawa, T, Naldi, A, Narenthiran, G, Natarajan, G, Nemetsky, E, Newcombe, V, Nielsen, N, Niznick, N, Noronha-Falcão, F, Nyquist, P, Olson, D, Othman, M, Owen, A, Padayachy, L, Pajoumand, M, Park, S, Pergakis, M, Perry, H, Polizzotto, L, Pouratian, N, Spivack, M, Prisco, L, Provencio, J, Puglises, F, Puybasset, L, Rao, C, Rasmussen, L, Rasulo, F, Ray, B, Ricci, Z, Richardson, R, Shinotsuka, C, Robba, C, Robertson, C, Rohaut, B, Rolston, J, Romagnoli, S, Rosanova, M, Rosenthal, E, Rowe, S, Rubin, M, Russell, M, Silva, G, Sanz, L, Sarasso, S, Sarwal, A, Schiff, N, Schnakers, C, Seder, D, Shah, V, Shapiro-Rosenbaubm, A, Shapshak, A, Sharma, K, Shutter, L, Sitt, J, Slomine, B, Smetana, K, Smielewski, P, Smith, W, Stamatakis, E, Steinberg, A, Stevens, R, Suarez, J, Sung, G, Sussman, B, Taran, S, Mazzeo, A, Thibaut, A, Thompson, D, Threlkeld, Z, Toker, D, Torbey, M, Tosto, J, Trevick, S, Tsaousi, G, Turgeon, A, Udy, A, Varelas, P, Videtta, W, Voss, H, Vox, F, Wagner, A, Wahlster, S, Wainwright, M, Whyte, J, Witherspoon, B, Yakhkind, A, Yeager, S, Young, M, Zafar, S, Zafonte, R, Zahuranec, D, Zammit, C, Zhang, B, Ziai, W, Zimmerman, L, Zink, E, Tinti, Lorenzo, Lawson, Thomas, Molteni, Erika, Kondziella, Daniel, Rass, Verena, Sharshar, Tarek, Bodien, Yelena G, Giacino, Joseph T, Mayer, Stephan A, Amiri, Moshgan, Muehlschlegel, Susanne, Venkatasubba Rao, Chethan P, Vespa, Paul M, Menon, David K, Citerio, Giuseppe, Helbok, Raimund, McNett, Molly, Agarwal, Sachin, Aiyagari, Venkatesh, Akbari, Yama, Albertson, Asher, Alexander, Sheila, Alexandrov, Anne, Alkhachroum, Ayham, Al-Mufti, Fawaz, Amiri, Moshagan, Appavu, Brian, Gebrewold, Meron Awraris, Ayounb, Marc, Badenes, Rafael, Bader, Mary Kay, Badjiata, Neeraj, Balu, Ram, Barlow, Brooke, Barra, Megan, Beekman, Rachel, Beghi, Ettore, Beqiri, Erta, Berlin, Tracey, Bilotta, Federico, Bleck, Thomas, Bodien, Yelena, Boerwinkle, Varina, Boly, Melanie, Bonnel, Alexandra, Brazzi, Luca, Brown, Emery, Bulic, Sebina, Caceres, Eder, Caceres, Adrian, Cafiero, Tullio, Carroll, Elizabeth, Cediel, Emilio G, Chou, Sherry, Claassen, Jan, Condie, Chad, Conti, Alfredo, Cosmas, Katie, Costa, Paolo, Creutzfeldt, Claire, Dangayach, Neha, Dauri, Mario, Debicki, Derek, DeGeorgia, Michael, Der-Nigoghossian, Caroline, Desai, Masoom, Dhar, Rajat, Diringer, Michael, Durr, Emily, Edlow, Brian, Ercole, Ari, Estraneo, Anna, Falcone, Guido, Farrokh, Salia, Ferguson, Adam, Fernandez-Espejo, Davinia, Fink, Ericka, Fins, Joseph, Foreman, Brandon, Franchi, Federico, Frontera, Jennifer, Ganesan, Rishi, Gaspard, Nicolas, Ghavam, Ahmeneh, Giacino, Joseph, Gibbons, Christie, Gilmore, Emily, Glustein, Chavie, Gosseries, Olivia, Green, Theresa, Greer, David, Guanci, Mary, Gupta, Deepak, Hahn, Cecil, Hakimi, Ryan, Hammond, Flora, Hanley, Daniel F, Hartings, Jed, Hassan, Ahmed, Hemphill, Claude, Da Cunha, Arthur Henrique Galvão Bruno, Hinson, Holly, Hirsch, Karen, Hocker, Sarah, Hu, Peter, Hu, Xiao, Human, Theresa, Hwang, David, Illes, Judy, Jaffa, Matthew, James, Michael L, Janas, Anna, Johnson, Susan, Jones, Morgan, Jox, Ralf J, Kalanuria, Atul, Keller, Emanuela, Kennedy, Lori, Kennelly, Megan, Keogh, Maggie, Kim, Jenn, Kim, Keri, Kirsch, Hannah, Kirschen, Matthew, Ko, Nerissa, Kreitzer, Natalie, Kromm, Julie, Kumar, Abhay, Kurtz, Pedro, Laureys, Steven, Lejeune, Nicolas, Lewis, Ariane, Liang, John, Ling, Geoffrey, Livesay, Sarah, Luppi, Andrea, MacDonald, Jennifer, Maddux, Craig, Mahanes, Dea, Mainali, Shraddha, Maldonado, Nelson, Ribeiro, Rennan Martins, Mascia, Luciana, Massimini, Marcello, Mathur, Rohan, Mayer, Stephan, McCredie, Victoria, Mejia-Mantilla, Jorge, Mendoza, Michael, Menon, David, Meyfroidt, Geert, Mijangos, Julio, Moberg, Dick, Moheet, Asma, Montalenti, Elisa, Monti, Martin, Morrison, Chris, Munar, Marina, Murtaugh, Brooke, Naccache, Lionel, Nagayama, Masao, Nairon, Emerson, Nakagawa, Thomas, Naldi, Andrea, Narenthiran, Ganesalingam, Natarajan, Girija, Nemetsky, Esther, Newcombe, Virginia, Nielsen, Niklas, Niznick, Naomi, Noronha-Falcão, Filipa, Nyquist, Paul, Olson, DaiWai, Othman, Marwan, Owen, Adrian, Padayachy, Llewellyn, Pajoumand, Mehrnaz, Park, Soojin, Pergakis, Melissa, Perry, Heidi, Polizzotto, Len, Pouratian, Nader, Spivack, Marilyn Price, Prisco, Lara, Provencio, Javier, Puglises, Francesco, Puybasset, Louis, Rao, Chethan, Rasmussen, Lindsay, Rasulo, Frank, Ray, Bappaditya, Ricci, Zaccaria, Richardson, Risa, Shinotsuka, Cassia Righy, Robba, Chiara, Robertson, Courtney, Rohaut, Benjamin, Rolston, John, Romagnoli, Stefano, Rosanova, Mario, Rosenthal, Eric, Rowe, Shaun, Rubin, Michael, Russell, Mary Beth, Silva, Gisele Sampaio, Sanz, Leandro, Sarasso, Simone, Sarwal, Aarti, Schiff, Nicolas, Schnakers, Caroline, Seder, David, Shah, Vishank Arun, Shapiro-Rosenbaubm, Amy, Shapshak, Angela, Sharma, Kartavya, Sharma, Kumar Ajay, Shutter, Lori, Sitt, Jacobo, Slomine, Beth, Smetana, Keaton, Smielewski, Peter, Smith, Wade, Stamatakis, Emmanuel, Steinberg, Alexis, Stevens, Robert, Suarez, Jose, Sung, Gene, Sussman, Bethany, Taran, Shaurya, Mazzeo, Anna Teresa, Thibaut, Aurore, Thompson, David, Threlkeld, Zachary, Toker, Daniel, Torbey, Michel, Tosto, Jenna, Trevick, Stephen, Tsaousi, Georgia, Turgeon, Alexis, Udy, Andrew, Varelas, Panos, Vespa, Paul, Videtta, Walter, Voss, Henning, Vox, Ford, Wagner, Amy, Wahlster, Sarah, Wainwright, Mark, Whyte, John, Witherspoon, Briana, Yakhkind, Aleksandra (Sasha), Yeager, Susan, Young, Michael, Zafar, Sahar, Zafonte, Ross, Zahuranec, Darin, Zammit, Chris, Zhang, Bei, Ziai, Wendy, Zimmerman, Lara, and Zink, Elizabeth

Abstract

Disorders of consciousness are neurological conditions characterized by impaired arousal and awareness of self and environment. Behavioural responses are absent or are present but fluctuate. Disorders of consciousness are commonly encountered as a consequence of both acute and chronic brain injuries, yet reliable epidemiological estimates would require inclusive, operational definitions of the concept, as well as wider knowledge dissemination among involved professionals. Whereas several manifestations have been described, including coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state, a comprehensive neurobiological definition for disorders of consciousness is still lacking. The scientific literature is primarily observational, and studies-specific aetiologies lead to disorders of consciousness. Despite advances in these disease-related forms, there remains uncertainty about whether disorders of consciousness are a disease-agnostic unitary entity with a common mechanism, prognosis or treatment response paradigm. Our knowledge of disorders of consciousness has also been hampered by heterogeneity of study designs, variables, and outcomes, leading to results that are not comparable for evidence synthesis. The different backgrounds of professionals caring for patients with disorders of consciousness and the different goals at different stages of care could partly explain this variability. The Prospective Studies working group of the Neurocritical Care Society Curing Coma Campaign was established to create a platform for observational studies and future clinical trials on disorders of consciousness and coma across the continuum of care. In this narrative review, the author panel presents limitations of prior observational clinical research and outlines practical considerations for future investigations. A narrative review format was selected to ensure that the full breadth of study design considerations could be addressed and to facilit

Published
2024

41. Critical errors in infrequently performed trauma procedures after training

Author

Anazodo, Amechi, Bonds, Brandon, Granite, Guinevere, Hagegeorge, George, Holmes, Megan, Hu, Peter, Jessie, Elliot, Longinaker, Nyaradzo, Monoson, Alexys, Narayan, Mayur, Pasley, Jason, Pielago, Joseph, Robinson, Eric, Romagnoli, Anna, Sarani, Babak, Squyres, Nicole, Teeter, William, Yang, Shiming, Mackenzie, Colin F., Shackelford, Stacy A., Tisherman, Samuel A., Puche, Adam, Elster, Eric A., and Bowyer, Mark W.

Published
2019
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47. Magnetic Resonance Imaging Lesions Associated With Paroxysmal Sympathetic Hyperactivity After Traumatic Brain Injury

Author

Podell, Jamie E., primary, Moffet, Eric W., additional, Bodanapally, Uttam K., additional, Pajoumand, Mehrnaz, additional, Silva, Luisa M., additional, Hu, Peter, additional, Chen, Lujie K., additional, Morris, Nicholas A., additional, Parikh, Gunjan, additional, Schwartzbauer, Gary T., additional, Aarabi, Bizhan, additional, and Badjatia, Neeraj, additional

Published
2024
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50. Artificial intelligence-based digital pathology for the detection and quantification of soil-transmitted helminths eggs.

Author

Cure-Bolt, Nancy, Perez, Fernando, Broadfield, Lindsay A., Levecke, Bruno, Hu, Peter, Oleynick, John, Beltrán, María, Ward, Peter, and Stuyver, Lieven

Subjects
ARTIFICIAL intelligence, SCHOOL children, INTESTINAL infections, NEGLECTED diseases, ASCARIS lumbricoides
Abstract

Background: Conventional microscopy of Kato-Katz (KK1.0) thick smears, the primary method for diagnosing soil-transmitted helminth (STH) infections, has limited sensitivity and is error-prone. Artificial intelligence-based digital pathology (AI-DP) may overcome the constraints of traditional microscopy-based diagnostics. This study in Ucayali, a remote Amazonian region of Peru, compares the performance of AI-DP-based Kato-Katz (KK2.0) method to KK1.0 at diagnosing STH infections in school-aged children (SAC). Methods: In this prospective, non-interventional study, 510 stool samples from SAC (aged 5–14 years) were analyzed using KK1.0, KK2.0, and tube spontaneous sedimentation technique (TSET). KK1.0 and KK2.0 slides were evaluated at 30-minute and 24-hour timepoints for detection of Ascaris lumbricoides, Trichuris trichiura, and hookworms (at 30-minute only). Diagnostic performance was assessed by measuring STH eggs per gram of stool (EPG), sensitivity of methods, and agreement between the methods. Results: KK2.0 detected more A. lumbricoides positive samples than KK1.0, with detection rates for T. trichiura and hookworms being comparable. At 30-minutes, 37.6%, 23.0%, and 2.6% of the samples tested positive based on KK1.0 for A. lumbricoides, T. trichiura, and hookworms, while this was 49.8%, 24.4%, and 1.9% for KK2.0. At 24-hours, 37.1% and 27.1% of the samples tested positive based on KK1.0 for A. lumbricoides and T. trichiura, while this was 45.8% and 24.1% for KK2.0. Mean EPG between KK2.0 and KK1.0 were not statistically different across STH species and timepoints, except for T. trichiura at 24-hours (higher mean EPG for KK1.0, p = 0.036). When considering infection intensity levels, KK2.0 identified 10% more of the total population as low-infection intensity samples of A. lumbricoides than KK1.0 (p ≤ 0.001, both timepoints) and similar to KK1.0 for T. trichiura and hookworms. Varying agreement existed between KK1.0 and KK2.0 in detecting STH eggs (A. lumbricoides: moderate; T. trichiura: substantial; hookworms: slight). However, these findings should be interpreted carefully as there are certain limitations that may have impacted the results of this study. Conclusions: This study demonstrates the potential of the AI-DP-based method for STH diagnosis. While similar to KK1.0, the AI-DP-based method outperforms it in certain aspects. These findings underscore the potential of advancing the AI-DP KK2.0 prototype for dependable STH diagnosis and furthering the development of automated digital microscopes in accordance with WHO guidelines for STH diagnosis. Author summary: In tropical and sub-tropical regions with limited access to clean potable water, hygiene, and sanitation, infections with intestinal worms (e.g. giant roundworm, whipworm, and hookworms) are widespread, primarily affecting school-aged children (SAC). These infections lead to malnutrition, anemia, and developmental issues. The World Health Organization (WHO) introduced a strategy in 2020 to control intestinal worm infections, emphasizing the need for accurate diagnostic tests. The current recommended method, Kato-Katz (KK1.0), though cost-effective, has limitations in terms of reproducibility and sensitivity. To address this, an artificial intelligence digital pathology (AI-DP)-based Kato-Katz method (KK2.0) was developed to enhance diagnostic accuracy. This study in Ucayali (Amazonian region of Peru) evaluated KK2.0's performance compared to KK1.0 in detecting intestinal worm infections among SAC. Stool samples from 510 SAC (5–14 years) were collected and analyzed using KK1.0 and KK2.0. KK2.0 demonstrated comparable diagnostic performance to KK1.0, with higher sensitivity for low-intensity giant roundworm infections. Prevalence rates differed between KK2.0 and KK1.0, indicating KK2.0's potential to identify additional infections. Overall, the findings suggest KK2.0's effectiveness in diagnosing STH infections, highlighting its potential to improve surveillance and treatment programs. Further research should address technical issues and assess KK2.0 in diverse settings, advancing its application for neglected tropical disease diagnosis. [ABSTRACT FROM AUTHOR]

Published
2024
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