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1,448 results on '"Cai, Hui"'

1. Realizing tunable Fermi level in SnTe by defect control

Author

Onipede, Bamidele Oluwagbenga, Metcalf, Matthew, Fletcher, Nisha, and Cai, Hui

Subjects
Condensed Matter - Materials Science
Abstract

The tuning of the Fermi level in tin telluride, a topological crystalline insulator, is essential for accessing its unique surface states and optimizing its electronic properties for applications such as spintronics and quantum computing. In this study, we demonstrate that the Fermi level in tin telluride can be effectively modulated by controlling the tin concentration during chemical vapor deposition synthesis. By introducing tin-rich conditions, we observed a blue shift in the X-ray photoelectron spectroscopy core-level peaks of both tin and tellurium, indicating an upward shift in the Fermi level. This shift is corroborated by a decrease in work function values measured via ultraviolet photoelectron spectroscopy, confirming the suppression of Sn vacancies. Our findings provide a low-cost, scalable method to achieve tunable Fermi levels in tin telluride, offering a significant advancement in the development of materials with tailored electronic properties for next-generation technological applications.

Published
2024

2. Efficient Knowledge Infusion via KG-LLM Alignment

Author

Jiang, Zhouyu, Zhong, Ling, Sun, Mengshu, Xu, Jun, Sun, Rui, Cai, Hui, Luo, Shuhan, and Zhang, Zhiqiang

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

To tackle the problem of domain-specific knowledge scarcity within large language models (LLMs), knowledge graph-retrievalaugmented method has been proven to be an effective and efficient technique for knowledge infusion. However, existing approaches face two primary challenges: knowledge mismatch between public available knowledge graphs and the specific domain of the task at hand, and poor information compliance of LLMs with knowledge graphs. In this paper, we leverage a small set of labeled samples and a large-scale corpus to efficiently construct domain-specific knowledge graphs by an LLM, addressing the issue of knowledge mismatch. Additionally, we propose a three-stage KG-LLM alignment strategyto enhance the LLM's capability to utilize information from knowledge graphs. We conduct experiments with a limited-sample setting on two biomedical question-answering datasets, and the results demonstrate that our approach outperforms existing baselines., Comment: ACL2024 Findings

Published
2024

5. Family history and gastric cancer incidence and mortality in Asia: a pooled analysis of more than half a million participants

Author

Huang, Dan, Song, Minkyo, Abe, Sarah Krull, Rahman, Md. Shafiur, Islam, Md. Rashedul, Saito, Eiko, De la Torre, Katherine, Sawada, Norie, Tamakoshi, Akiko, Shu, Xiao-Ou, Cai, Hui, Hozawa, Atsushi, Kanemura, Seiki, Kim, Jeongseon, Chen, Yu, Ito, Hidemi, Sugawara, Yumi, Park, Sue K., Shin, Myung-Hee, Hirabayashi, Mayo, Kimura, Takashi, Gao, Yu-Tang, Wen, Wanqing, Oze, Isao, Shin, Aesun, Ahn, Yoon-Ok, Ahsan, Habibul, Boffetta, Paolo, Chia, Kee Seng, Matsuo, Keitaro, Qiao, You-Lin, Rothman, Nathaniel, Zheng, Wei, Inoue, Manami, and Kang, Daehee

Published
2024
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7. Reverse Chain: A Generic-Rule for LLMs to Master Multi-API Planning

Author

Zhang, Yinger, Cai, Hui, Song, Xeirui, Chen, Yicheng, Sun, Rui, and Zheng, Jing

Subjects
Computer Science - Software Engineering, Computer Science - Artificial Intelligence, Computer Science - Programming Languages
Abstract

While enabling large language models to implement function calling (known as APIs) can greatly enhance the performance of Large Language Models (LLMs), function calling is still a challenging task due to the complicated relations between different APIs, especially in a context-learning setting without fine-tuning. This paper introduces ``Reverse Chain'', a controllable, target-driven approach designed to empower LLMs with the capability to operate external APIs only via prompts. Recognizing that most LLMs have limited tool-use capabilities, Reverse Chain limits LLMs to executing simple tasks, e.g., API Selection and Argument Completion. Furthermore, to manage a controllable multi-function calling, Reverse Chain adopts a generic rule based on a backward reasoning process. This rule determines when to do API selection or Argument completion. To evaluate the multi-tool-use capability of LLMs, we have released a compositional multi-tool task dataset, available at \url{https://anonymous.4open.science/r/reverse-chain-8681}. Extensive numerical experiments validate the remarkable proficiency of Reverse Chain in managing multiple API calls.

Published
2023

8. A Deeping Learning Modeling for the Development of Emotion judgement in Autistic Children

Author

Cai, Hui-Xin, Chen, TSE MING, FENG, HUA, Peng, Shu-Ling, Huang, Po-Sheng, Wang, Ying-Chien, and Hu, Jon-Fan

Subjects
Psychology, Emotion, Computational Modeling, Eye tracking
Abstract

In general, it is still unclear, to what extent, that autistic children would develop the ability to recognize facial expression by age and which basic emotion expressions are consistently difficult to learn. Moreover, what crucial processing and mechanisms would play a key role for the autistic behavior patterns in early social interaction. To answer these questions, a deep learning model is constructed to simulate the eye movement records during judging emotion expression of typical developed and autistic children. The simulation results are: 1. for older autistic models, if the gaze fixations for eyes and mouth of positive emotion is longer, it would lead to greater recognition performance; 2. in contrast, for younger autistic models, it takes longer training sessions to correctly recognize most of negative emotions as too much inferences of internal information occurred while establishing reliable prototypes of facial figures in differentiating the angry, sad, and disgusting expressions.

Published
2024

17. Restoration of a dental defect in a patient with ectodermal dysplasia: a case report and literature review

Author

LV Hong, LIU Qinghui, LI Jiafu, CAI Hui, BU Honghu, PU Yiming, GUO Jincai

Subjects
ectodermal dysplasia, dentition defect, missing tooth, congenital tooth loss removable, partial dentures, digital guides, oral implant, oral restoration, implant covered dentures, Medicine
Abstract

Objective To explore the treatment options for congenitally missing teeth in patients with ectodermal dysplasia and provide a clinical reference. Methods A patient with ectodermal dysplasia with a concave midface, anterior protrusion of the chin, and underdevelopment of the lower third of the face presented with congenital loss of multiple maxillary teeth, malocclusion of the remaining teeth, congenital loss of mandibular dentition, small dental arches, and upper and lower alveolar bone hypoplasia. The patient was treated by means of a removable partial maxillary prosthesis, implants in the anterior region of the lower mandible designed with the assistance of digital guides, and bar-clamped implant-overlay prostheses. A literature review of the protocol for the treatment of this condition was also conducted. Results In addition to good retention and stability after denture wear, an excellent occlusal relationship, improvement of the patient's facial appearance, including upper and lower lip fullness, more equal balancing of the lower and middle 1/3 of the face, and improved masticatory function were achieved. The results of the literature review showed that patients with ectodermal dysplasia who are congenitally edentulous usually have a complex intraoral situation that makes restoration difficult, and common restorative modalities for these patients include fixed bridges, removable partial dentures, complete dentures, overdentures, and implant prostheses, which need to be selected according to the actual intraoral situation of each patient. Currently, there is no consensus on the treatment of congenitally missing teeth in patients with ectodermal dysplasia, and some scholars have suggested that fixed restorations be recommended for patients with fewer missing teeth, while the option of removable or implant-covered denture restorations should be given to patients with more missing teeth, with removeable prostheses for underage patients that are replaced with permanent fixed prostheses when the jaws have stabilized. Conclusion In patients with ectodermal dysplasia with congenital tooth loss, all factors should be taken into account, and an individualized restorative plan should be developed.

Published
2024
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19. A method for reducing torque ripple of switched reluctance motor based on partitioned TSF

Author

Cai Hui, Han Yanjie, Pan Yinbin, and Zean Tao

Subjects
switched reluctance motor, torque sharing function, torque ripple minimization, torque control, optimization, General Works
Abstract

In this paper, a new torque sharing function control strategy is proposed to reduce the torque ripple. The traditional torque ripple methods, such as exponential and linear torque allocation strategies, the torque generation capacity of each phase and the power limitation of the power converter is not taken into account, in this paper, the communication region is divided into three intervals by establishing a new partitioning standard. According to the re-established reference function of torque generation, the torque deviation caused by phase current tracking error is compensated according to the torque generation capacity. Both optimization of torque ripple suppression and copper loss minimization are taken into consideration in this paper. To verify the validity and performances of the proposed TSF methods, simulations and experiments have been implemented in a 12/8 structure Switched Reluctance Motor prototype. This method can be applied to other switched reluctance motors with different topologies. Result shows lower current tracking error and better performance of torque ripple minimization compared with the conventional two-interval compensation method.

Published
2024
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20. Investigation of Deformation and Fracture Mechanisms in Two-dimensional Gallium Telluride Multilayers Using Nanoindentation

Author

Zhou, Yan, Zhou, Shi, Ying, Penghua, Zhao, Qinghua, Xie, Yong, Gong, Mingming, Jiang, Pisu, Cai, Hui, Chen, Bin, Tongay, Sefaattin, Jie, Wanqi, Zhang, Jin, Wang, Tao, Liu, Dong, and Kuball, Martin

Subjects
Condensed Matter - Materials Science
Abstract

Two-dimensional (2D) materials possess great potential for flexible devices, ascribing to their outstanding electrical, optical, and mechanical properties. However, their mechanical deformation property and fracture mechanism, which are inescapable in many applications like flexible optoelectronics, are still unclear or not thoroughly investigated due methodology limitations. In light of this, such mechanical properties and mechanisms are explored on example of gallium telluride (GaTe), a promising optoelectronic candidate with an ultrahigh photo-responsibility and a high plasticity within 2D family. Considering the driving force insufficient in atomic force microscopy (AFM)-based nanoindentation method, here the mechanical properties of both substrate-supported and suspended GaTe multilayers were systematically investigated through full-scale Berkovich-tip nanoindentation, micro-Raman spectroscopy, AFM, and scanning electron microscopy. An unusual concurrence of multiple pop-in and load-drop events in loading curve was observed. By further correlating to molecular dynamics calculations, this concurrence was unveiled originating from the interlayer sliding mediated layers-by-layers fracture mechanism within GaTe multilayers. The van der Waals force between GaTe multilayers and substrates was revealed much stronger than that between GaTe interlayers, resulting in the easy sliding and fracture of multilayers within GaTe. This work provides new insights into the deformation and fracture mechanisms of GaTe and other similar 2D multilayers in flexible applications., Comment: 21 pages, 5 figures

Published
2022
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21. Breast Cancer Molecular Subtypes Prediction on Pathological Images with Discriminative Patch Selecting and Multi-Instance Learning

Author

Liu, Hong, Xu, Wen-Dong, Shang, Zi-Hao, Wang, Xiang-Dong, Zhou, Hai-Yan, Ma, Ke-Wen, Zhou, Huan, Qi, Jia-Lin, Jiang, Jia-Rui, Tan, Li-Lan, Zeng, Hui-Min, Cai, Hui-Juan, Wang, Kuan-Song, and Qian, Yue-Liang

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Molecular subtypes of breast cancer are important references to personalized clinical treatment. For cost and labor savings, only one of the patient's paraffin blocks is usually selected for subsequent immunohistochemistry (IHC) to obtain molecular subtypes. Inevitable sampling error is risky due to tumor heterogeneity and could result in a delay in treatment. Molecular subtype prediction from conventional H&E pathological whole slide images (WSI) using AI method is useful and critical to assist pathologists pre-screen proper paraffin block for IHC. It's a challenging task since only WSI level labels of molecular subtypes can be obtained from IHC. Gigapixel WSIs are divided into a huge number of patches to be computationally feasible for deep learning. While with coarse slide-level labels, patch-based methods may suffer from abundant noise patches, such as folds, overstained regions, or non-tumor tissues. A weakly supervised learning framework based on discriminative patch selecting and multi-instance learning was proposed for breast cancer molecular subtype prediction from H&E WSIs. Firstly, co-teaching strategy was adopted to learn molecular subtype representations and filter out noise patches. Then, a balanced sampling strategy was used to handle the imbalance in subtypes in the dataset. In addition, a noise patch filtering algorithm that used local outlier factor based on cluster centers was proposed to further select discriminative patches. Finally, a loss function integrating patch with slide constraint information was used to finetune MIL framework on obtained discriminative patches and further improve the performance of molecular subtyping. The experimental results confirmed the effectiveness of the proposed method and our models outperformed even senior pathologists, with potential to assist pathologists to pre-screen paraffin blocks for IHC in clinic.

Published
2022

22. A saturated map of common genetic variants associated with human height

Author

Yengo, Loïc, Vedantam, Sailaja, Marouli, Eirini, Sidorenko, Julia, Bartell, Eric, Sakaue, Saori, Graff, Marielisa, Eliasen, Anders U, Jiang, Yunxuan, Raghavan, Sridharan, Miao, Jenkai, Arias, Joshua D, Graham, Sarah E, Mukamel, Ronen E, Spracklen, Cassandra N, Yin, Xianyong, Chen, Shyh-Huei, Ferreira, Teresa, Highland, Heather H, Ji, Yingjie, Karaderi, Tugce, Lin, Kuang, Lüll, Kreete, Malden, Deborah E, Medina-Gomez, Carolina, Machado, Moara, Moore, Amy, Rüeger, Sina, Sim, Xueling, Vrieze, Scott, Ahluwalia, Tarunveer S, Akiyama, Masato, Allison, Matthew A, Alvarez, Marcus, Andersen, Mette K, Ani, Alireza, Appadurai, Vivek, Arbeeva, Liubov, Bhaskar, Seema, Bielak, Lawrence F, Bollepalli, Sailalitha, Bonnycastle, Lori L, Bork-Jensen, Jette, Bradfield, Jonathan P, Bradford, Yuki, Braund, Peter S, Brody, Jennifer A, Burgdorf, Kristoffer S, Cade, Brian E, Cai, Hui, Cai, Qiuyin, Campbell, Archie, Cañadas-Garre, Marisa, Catamo, Eulalia, Chai, Jin-Fang, Chai, Xiaoran, Chang, Li-Ching, Chang, Yi-Cheng, Chen, Chien-Hsiun, Chesi, Alessandra, Choi, Seung Hoan, Chung, Ren-Hua, Cocca, Massimiliano, Concas, Maria Pina, Couture, Christian, Cuellar-Partida, Gabriel, Danning, Rebecca, Daw, E Warwick, Degenhard, Frauke, Delgado, Graciela E, Delitala, Alessandro, Demirkan, Ayse, Deng, Xuan, Devineni, Poornima, Dietl, Alexander, Dimitriou, Maria, Dimitrov, Latchezar, Dorajoo, Rajkumar, Ekici, Arif B, Engmann, Jorgen E, Fairhurst-Hunter, Zammy, Farmaki, Aliki-Eleni, Faul, Jessica D, Fernandez-Lopez, Juan-Carlos, Forer, Lukas, Francescatto, Margherita, Freitag-Wolf, Sandra, Fuchsberger, Christian, Galesloot, Tessel E, Gao, Yan, Gao, Zishan, Geller, Frank, Giannakopoulou, Olga, Giulianini, Franco, Gjesing, Anette P, Goel, Anuj, Gordon, Scott D, Gorski, Mathias, Grove, Jakob, and Guo, Xiuqing

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Humans, Body Height, Gene Frequency, Genome, Human, Genome-Wide Association Study, Haplotypes, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Europe, Sample Size, Phenotype, Chromosome Mapping, 23andMe Research Team, VA Million Veteran Program, DiscovEHR, eMERGE, Lifelines Cohort Study, PRACTICAL Consortium, Understanding Society Scientific Group, General Science & Technology
Abstract

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Published
2022

36. Unusual Deformation and Fracture in Gallium Telluride Multilayers

Author

Zhou, Yan, Zhou, Shi, Ying, Penghua, Zhao, Qinghua, Xie, Yong, Gong, Mingming, Jiang, Pisu, Cai, Hui, Chen, Bin, Tongay, Sefaattin, Zhang, Jin, Jie, Wanqi, Wang, Tao, Tan, Pingheng, Liu, Dong, and Kuball, Martin

Subjects
Physical Sciences, Chemical Sciences, Chemical sciences, Physical sciences
Abstract

The deformation and fracture mechanism of two-dimensional (2D) materials are still unclear and not thoroughly investigated. Given this, mechanical properties and mechanisms are explored on example of gallium telluride (GaTe), a promising 2D semiconductor with an ultrahigh photoresponsivity and a high flexibility. Hereby, the mechanical properties of both substrate-supported and suspended GaTe multilayers were investigated through Berkovich-tip nanoindentation instead of the commonly used AFM-based nanoindentation method. An unusual concurrence of multiple pop-in and load-drop events in loading curve was observed. Theoretical calculations unveiled this concurrence originating from the interlayer-sliding mediated layers-by-layers fracture mechanism in GaTe multilayers. The van der Waals force dominated interlayer interactions between GaTe and substrates was revealed much stronger than that between GaTe interlayers, resulting in the easy sliding and fracture of multilayers within GaTe. This work introduces new insights into the deformation and fracture of GaTe and other 2D materials in flexible electronics applications.

Published
2022

37. Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Author

Dareng, Eileen O, Tyrer, Jonathan P, Barnes, Daniel R, Jones, Michelle R, Yang, Xin, Aben, Katja KH, Adank, Muriel A, Agata, Simona, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Aravantinos, Gerasimos, Arun, Banu K, Augustinsson, Annelie, Balmaña, Judith, Bandera, Elisa V, Barkardottir, Rosa B, Barrowdale, Daniel, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bermisheva, Marina, Bernardini, Marcus Q, Bjorge, Line, Black, Amanda, Bogdanova, Natalia V, Bonanni, Bernardo, Borg, Ake, Brenton, James D, Budzilowska, Agnieszka, Butzow, Ralf, Buys, Saundra S, Cai, Hui, Caligo, Maria A, Campbell, Ian, Cannioto, Rikki, Cassingham, Hayley, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Kexin, Chiew, Yoke-Eng, Chung, Wendy K, Claes, Kathleen BM, Colonna, Sarah, Cook, Linda S, Couch, Fergus J, Daly, Mary B, Dao, Fanny, Davies, Eleanor, de la Hoya, Miguel, de Putter, Robin, Dennis, Joe, DePersia, Allison, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Doherty, Jennifer A, Domchek, Susan M, Dörk, Thilo, du Bois, Andreas, Dürst, Matthias, Eccles, Diana M, Eliassen, Heather A, Engel, Christoph, Evans, Gareth D, Fasching, Peter A, Flanagan, James M, Fortner, Renée T, Machackova, Eva, Friedman, Eitan, Ganz, Patricia A, Garber, Judy, Gensini, Francesca, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goodman, Marc T, Greene, Mark H, Gronwald, Jacek, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Hansen, Thomas VO, Harris, Holly R, Hartman, Mikael, Heitz, Florian, Hildebrandt, Michelle AT, Høgdall, Estrid, Høgdall, Claus K, Hopper, John L, Huang, Ruea-Yea, Huff, Chad, Hulick, Peter J, Huntsman, David G, Imyanitov, Evgeny N, Isaacs, Claudine, Jakubowska, Anna, James, Paul A, and Janavicius, Ramunas

Subjects
GEMO Study Collaborators, GC-HBOC Study Collaborators, EMBRACE Collaborators, OPAL Study Group, AOCS Group, KConFab Investigators, HEBON Investigators, OCAC Consortium, CIMBA Consortium, Genetics, Clinical Sciences, Genetics & Heredity
Published
2022

46. Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

Author

Dareng, Eileen O., Coetzee, Simon G., Tyrer, Jonathan P., Peng, Pei-Chen, Rosenow, Will, Chen, Stephanie, Davis, Brian D., Dezem, Felipe Segato, Seo, Ji-Heui, Nameki, Robbin, Reyes, Alberto L., Aben, Katja K.H., Anton-Culver, Hoda, Antonenkova, Natalia N., Aravantinos, Gerasimos, Bandera, Elisa V., Beane Freeman, Laura E., Beckmann, Matthias W., Beeghly-Fadiel, Alicia, Benitez, Javier, Bernardini, Marcus Q., Bjorge, Line, Black, Amanda, Bogdanova, Natalia V., Bolton, Kelly L., Brenton, James D., Budzilowska, Agnieszka, Butzow, Ralf, Cai, Hui, Campbell, Ian, Cannioto, Rikki, Chang-Claude, Jenny, Chanock, Stephen J., Chen, Kexin, Chenevix-Trench, Georgia, Chiew, Yoke-Eng, Cook, Linda S., DeFazio, Anna, Dennis, Joe, Doherty, Jennifer A., Dörk, Thilo, du Bois, Andreas, Dürst, Matthias, Eccles, Diana M., Ene, Gabrielle, Fasching, Peter A., Flanagan, James M., Fortner, Renée T., Fostira, Florentia, Gentry-Maharaj, Aleksandra, Giles, Graham G., Goodman, Marc T., Gronwald, Jacek, Haiman, Christopher A., Håkansson, Niclas, Heitz, Florian, Hildebrandt, Michelle A.T., Høgdall, Estrid, Høgdall, Claus K., Huang, Ruea-Yea, Jensen, Allan, Jones, Michael E., Kang, Daehee, Karlan, Beth Y., Karnezis, Anthony N., Kelemen, Linda E., Kennedy, Catherine J., Khusnutdinova, Elza K., Kiemeney, Lambertus A., Kjaer, Susanne K., Kupryjanczyk, Jolanta, Labrie, Marilyne, Lambrechts, Diether, Larson, Melissa C., Le, Nhu D., Lester, Jenny, Li, Lian, Lubiński, Jan, Lush, Michael, Marks, Jeffrey R., Matsuo, Keitaro, May, Taymaa, McLaughlin, John R., McNeish, Iain A., Menon, Usha, Missmer, Stacey, Modugno, Francesmary, Moffitt, Melissa, Monteiro, Alvaro N., Moysich, Kirsten B., Narod, Steven A., Nguyen-Dumont, Tu, Odunsi, Kunle, Olsson, Håkan, Onland-Moret, N. Charlotte, Park, Sue K., Pejovic, Tanja, Permuth, Jennifer B., Piskorz, Anna, Prokofyeva, Darya, Riggan, Marjorie J., Risch, Harvey A., Rodríguez-Antona, Cristina, Rossing, Mary Anne, Sandler, Dale P., Setiawan, V. Wendy, Shan, Kang, Song, Honglin, Southey, Melissa C., Steed, Helen, Sutphen, Rebecca, Swerdlow, Anthony J., Teo, Soo Hwang, Terry, Kathryn L., Thompson, Pamela J., Vestrheim Thomsen, Liv Cecilie, Titus, Linda, Trabert, Britton, Travis, Ruth, Tworoger, Shelley S., Valen, Ellen, Van Nieuwenhuysen, Els, Edwards, Digna Velez, Vierkant, Robert A., Webb, Penelope M., Weinberg, Clarice R., Weise, Rayna Matsuno, Wentzensen, Nicolas, White, Emily, Winham, Stacey J., Wolk, Alicja, Woo, Yin-Ling, Wu, Anna H., Yan, Li, Yannoukakos, Drakoulis, Zeinomar, Nur, Zheng, Wei, Ziogas, Argyrios, Berchuck, Andrew, Goode, Ellen L., Huntsman, David G., Pearce, Celeste L., Ramus, Susan J., Sellers, Thomas A., Freedman, Matthew L., Lawrenson, Kate, Schildkraut, Joellen M., Hazelett, Dennis, Plummer, Jasmine T., Kar, Siddhartha, Jones, Michelle R., Pharoah, Paul D.P., and Gayther, Simon A.

Published
2024
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