Benjamin S. Glicksberg

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 58

Top Topics

Electronic Health Records

Intensive Care Unit

Top Venues

npj Digit. Medicine

Publications

Wonsuk Oh, Pushkala Jayaraman, Pranai Tandon, Udit S. Chaddha, Patricia H. Kovatch, Alexander W. Charney, Benjamin S. Glicksberg, Girish N. Nadkarni
A novel method leveraging time series data to improve subphenotyping and application in critically ill patients with COVID-19. Artif. Intell. Medicine 148 (2024)
Akhil Vaid, Joshua Lampert, Juhee Lee, Ashwin Sawant, Donald Apakama, Ankit Sakhuja, Ali Soroush, Denise Lee, Isotta Landi, Nicole Bussola, Ismail Nabeel, Robbie Freeman, Patricia H. Kovatch, Brendan G. Carr, Benjamin S. Glicksberg, Edgar Argulian, Stamatios Lerakis, Monica Kraft, Alexander Charney, Girish N. Nadkarni
Generative Large Language Models are autonomous practitioners of evidence-based medicine. CoRR (2024)
Shiavax J. Rao, Ameesh Isath, Parvathy Krishnan, Jonathan A. Tangsrivimol, Hafeez Ul Hassan Virk, Zhen Wang, Benjamin S. Glicksberg, Chayakrit Krittanawong
ChatGPT: A Conceptual Review of Applications and Utility in the Field of Medicine. J. Medical Syst. 48 (1) (2024)
Faris F. Gulamali, Ashwin Sawant, Ira Hofer, Matthew A. Levin, Alexander Charney, Karandeep Singh, Benjamin S. Glicksberg, Girish N. Nadkarni
Online Unsupervised Representation Learning of Waveforms in the Intensive Care Unit via a novel cooperative framework: Spatially Resolved Temporal Networks (SpaRTEn). MLHC (2023)
Lauren M. Sanders, Ryan T. Scott, Jason H. Yang, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart J. Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Seung-Min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes
Biological research and self-driving labs in deep space supported by artificial intelligence. Nat. Mac. Intell. 5 (3) (2023)
Zhe He, Rui Zhang, Gayo Diallo, Zhengxing Huang, Benjamin S. Glicksberg
Editorial: Explainable artificial intelligence for critical healthcare applications. Frontiers Artif. Intell. 6 (2023)
Akhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua Lampert, Alexander Charney, Hayit Greenspan, Jagat Narula, Benjamin S. Glicksberg, Girish N. Nadkarni
A foundational vision transformer improves diagnostic performance for electrocardiograms. npj Digit. Medicine 6 (2023)
Tingyi Wanyan, Mingquan Lin, Ying Ding, Benjamin S. Glicksberg, Fei Wang, Yifan Peng
Optimizing Embedding Space with Sub-categorical Supervised Pre-training: A Theoretical Approach Towards Improving Sepsis Prediction. ICHI (2023)
Sonish Sivarajkumar, Pratyush Tandale, Ankit Bhardwaj, Kipp W. Johnson, Anoop Titus, Benjamin S. Glicksberg, Shameer Khader, Kamlesh K. Yadav, Lakshminarayanan Subramanian
Generation of a Compendium of Transcription Factor Cascades and Identification of Potential Therapeutic Targets using Graph Machine Learning. CoRR (2023)
Ryan T. Scott, Lauren M. Sanders, Erik L. Antonsen, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart J. Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte A. Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Michael Snyder, Frank Soboczenski, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes
Biomonitoring and precision health in deep space supported by artificial intelligence. Nat. Mac. Intell. 5 (3) (2023)
Tingyi Wanyan, Mingquan Lin, Eyal Klang, Kartikeya M. Menon, Faris F. Gulamali, Ariful Azad, Yiye Zhang, Ying Ding, Zhangyang Wang, Fei Wang, Benjamin S. Glicksberg, Yifan Peng
Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction. BCB (2022)
Faris F. Gulamali, Ashwin Sawant, Patricia A. Kovatch, Benjamin S. Glicksberg, Alexander Charney, Girish N. Nadkarni, Eric K. Oermann
Autoencoders for sample size estimation for fully connected neural network classifiers. npj Digit. Medicine 5 (2022)
Teja Ganta, Nicholas Genes, Benjamin S. Glicksberg, Rosamond Rhodes, Robbie Freeman, Bruce Darrow
Defining an Ethical Relationship with Artificial Intelligence at a Large Academic Health System. AMIA (2022)
Bar H. Ezra, Shreyas Havaldar, Benjamin S. Glicksberg, Nadav Rappoport
Multi-Dimensional Laboratory Test Score as a Proxy for Health. MIE (2022)
Junghwan Lee, Tingyi Wanyan, Qingyu Chen, Tiarnan D. L. Keenan, Benjamin S. Glicksberg, Emily Y. Chew, Zhiyong Lu, Fei Wang, Yifan Peng
Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning. MLMI@MICCAI (2022)
Yan Han, Chongyan Chen, Ahmed H. Tewfik, Benjamin S. Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop. WACV (2022)
Akhil Vaid, Joy Jiang, Ashwin Sawant, Stamatios Lerakis, Edgar Argulian, Yuri Ahuja, Joshua Lampert, Alexander Charney, Hayit Greenspan, Benjamin S. Glicksberg, Jagat Narula, Girish N. Nadkarni
HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes. CoRR (2022)
Tingyi Wanyan, Jing Zhang, Ying Ding, Ariful Azad, Zhangyang Wang, Benjamin S. Glicksberg
Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data. CoRR (2021)
Yan Han, Chongyan Chen, Ahmed H. Tewfik, Benjamin S. Glicksberg, Ying Ding, Yifan Peng, Zhangyang Wang
Cross-Modal Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop. CoRR (2021)
Jie Xu, Benjamin S. Glicksberg, Chang Su, Peter B. Walker, Jiang Bian, Fei Wang
Federated Learning for Healthcare Informatics. J. Heal. Informatics Res. 5 (1) (2021)
Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Jing Zhang, Riccardo Miotto, Zhangyang Wang, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
Contrastive learning improves critical event prediction in COVID-19 patients. Patterns 2 (12) (2021)
Tingyi Wanyan, Hossein Honarvar, Suraj K. Jaladanki, Chengxi Zang, Nidhi Naik, Sulaiman Somani, Jessica K. De Freitas, Ishan Paranjpe, Akhil Vaid, Riccardo Miotto, Girish N. Nadkarni, Marinka Zitnik, Ariful Azad, Fei Wang, Ying Ding, Benjamin S. Glicksberg
Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients. CoRR (2021)
Lauren A. Lepow, Braja Gopal Patra, Isotta Landi, Prakash Adekkanattu, Jyotishman Pathak, Mark Olfson, J. John Mann, Euijung Ryu, Joanna M. Biernacka, Girish N. Nadkarni, Priya Wickramaratne, Myrna Weissman, Benjamin S. Glicksberg, Alexander Charney
Extracting Social Isolation Information From Psychiatric Notes in the Electronic Health Records. AMIA (2021)
Tingyi Wanyan, Akhil Vaid, Jessica K. De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N. Nadkarni, Ariful Azad, Ying Ding, Benjamin S. Glicksberg
Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit. IEEE Trans. Big Data 7 (1) (2021)
Ryan T. Scott, Erik L. Antonsen, Lauren M. Sanders, Jaden J. A. Hastings, Seung-Min Park, Graham Mackintosh, Robert J. Reynolds, Adrienne L. Hoarfrost, Aenor Sawyer, Casey S. Greene, Benjamin S. Glicksberg, Corey A. Theriot, Daniel C. Berrios, Jack Miller, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Stuart Chalk, Guillermo M. Delgado-Aparicio, Melissa Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, John Kalantari, Kia Khezeli, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Héctor García Martín, Christopher E. Mason, Mona Matar, George I. Mias, Jerry G. Myers Jr., Charlotte Nelson, Jonathan Oribello, Patricia Parsons-Wingerter, R. K. Prabhu, Amina Ann Qutub, Jon Rask, Amanda Saravia-Butler, Suchi Saria, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Jason H. Yang, Marinka Zitnik, Sylvain V. Costes
Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health. CoRR (2021)
Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, Benjamin S. Glicksberg
Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records. Data Intell. 3 (3) (2021)
Ramya Dhatri Vunikili, Benjamin S. Glicksberg, Kipp W. Johnson, Joel T. Dudley, Lakshminarayanan Subramanian, Khader Shameer
Predictive Modelling of Susceptibility to Substance Abuse, Mortality and Drug-Drug Interactions in Opioid Patients. Frontiers Artif. Intell. 4 (2021)
Braja Gopal Patra, Mohit M. Sharma, Veer Vekaria, Prakash Adekkanattu, Olga V. Patterson, Benjamin S. Glicksberg, Lauren A. Lepow, Euijung Ryu, Joanna M. Biernacka, Al'ona Furmanchuk, Thomas J. George, William R. Hogan, Yonghui Wu, Xi Yang, Jiang Bian, Myrna Weissman, Priya Wickramaratne, J. John Mann, Mark Olfson, Thomas R. Campion Jr., Mark G. Weiner, Jyotishman Pathak
Extracting social determinants of health from electronic health records using natural language processing: a systematic review. J. Am. Medical Informatics Assoc. 28 (12) (2021)
Eyal Klang, Matthew A. Levin, Shelly Soffer, Alexis Zebrowski, Benjamin S. Glicksberg, Brendan G. Carr, Jolion Mcgreevy, David L. Reich, Robert Freeman
A Simple Free-Text-like Method for Extracting Semi-Structured Data from Electronic Health Records: Exemplified in Prediction of In-Hospital Mortality. Big Data Cogn. Comput. 5 (3) (2021)
Jessica K. De Freitas, Kipp W. Johnson, Eddye Golden, Girish N. Nadkarni, Joel T. Dudley, Erwin P. Bottinger, Benjamin S. Glicksberg, Riccardo Miotto
Phe2vec: Automated disease phenotyping based on unsupervised embeddings from electronic health records. Patterns 2 (9) (2021)
Yuan Luo, Fei Wang, Benjamin S. Glicksberg, Jessilyn Dunn, Nigam Shah
Multi-Modal Data Science for Healthcare: State of the Art, Challenges, and Opportunities. AMIA (2021)
Lauren M. Sanders, Jason H. Yang, Ryan T. Scott, Amina Ann Qutub, Héctor García Martín, Daniel C. Berrios, Jaden J. A. Hastings, Jon Rask, Graham Mackintosh, Adrienne L. Hoarfrost, Stuart Chalk, John Kalantari, Kia Khezeli, Erik L. Antonsen, Joel Babdor, Richard Barker, Sergio E. Baranzini, Afshin Beheshti, Guillermo M. Delgado-Aparicio, Benjamin S. Glicksberg, Casey S. Greene, Melissa A. Haendel, Arif A. Hamid, Philip Heller, Daniel Jamieson, Katelyn J. Jarvis, Svetlana V. Komarova, Matthieu Komorowski, Prachi Kothiyal, Ashish Mahabal, Uri Manor, Christopher E. Mason, Mona Matar, George I. Mias, Jack Miller, Jerry G. Myers Jr., Charlotte Nelson, Jonathan Oribello, Seung-min Park, Patricia Parsons-Wingerter, R. K. Prabhu, Robert J. Reynolds, Amanda Saravia-Butler, Suchi Saria, Aenor Sawyer, Nitin Kumar Singh, Frank Soboczenski, Michael Snyder, Karthik Soman, Corey A. Theriot, David Van Valen, Kasthuri Venkateswaran, Liz Warren, Liz Worthey, Marinka Zitnik, Sylvain V. Costes
Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs. CoRR (2021)
Hao-Chih Lee, Osamu Ichikawa, Benjamin S. Glicksberg, Aparna A. Divaraniya, Christine E. Becker, Pankaj Agarwal, Joel T. Dudley
Identification of therapeutic targets from genetic association studies using hierarchical component analysis. BioData Min. 13 (1) (2020)
Tingyi Wanyan, Martin Kang, Marcus A. Badgeley, Kipp W. Johnson, Jessica K. De Freitas, Fayzan F. Chaudhry, Akhil Vaid, Shan Zhao, Riccardo Miotto, Girish N. Nadkarni, Fei Wang, Justin F. Rousseau, Ariful Azad, Ying Ding, Benjamin S. Glicksberg
Heterogeneous Graph Embeddings of Electronic Health Records Improve Critical Care Disease Predictions. AIME (2020)
Beau Norgeot, Kathleen Muenzen, Thomas A. Peterson, Xuancheng Fan, Benjamin S. Glicksberg, Gundolf Schenk, Eugenia Rutenberg, Boris Oskotsky, Marina Sirota, Jinoos Yazdany, Gabriela Schmajuk, Dana Ludwig, Theodore C. Goldstein, Atul J. Butte
Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes. npj Digit. Medicine 3 (2020)
Tingyi Wanyan, Hossein Honarvar, Ariful Azad, Ying Ding, Benjamin S. Glicksberg
Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records. CoRR (2020)
Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee, Sarah T. Cherng, Giulia Landi, Matteo Danieletto, Joel T. Dudley, Cesare Furlanello, Riccardo Miotto
Deep representation learning of electronic health records to unlock patient stratification at scale. npj Digit. Medicine 3 (2020)
Isotta Landi, Benjamin S. Glicksberg, Hao-Chih Lee, Sarah T. Cherng, Giulia Landi, Matteo Danieletto, Joel T. Dudley, Cesare Furlanello, Riccardo Miotto
Deep Representation Learning of Electronic Health Records to Unlock Patient Stratification at Scale. CoRR (2020)
Fayzan F. Chaudhry, Matteo Danieletto, Eddye Golden, Jerome Scelza, Greg Botwin, Mark M. Shervey, Jessica K. De Freitas, Ishan Paranjpe, Girish N. Nadkarni, Riccardo Miotto, Patricia Glowe, Greg Stock, Bethany Percha, Noah Zimmerman, Joel T. Dudley, Benjamin S. Glicksberg
Sleep in the Natural Environment: A Pilot Study. Sensors 20 (5) (2020)
Andrew C. Liu, Krishna Patel, Ramya Dhatri Vunikili, Kipp W. Johnson, Fahad Abdu, Shivani Kamath Belman, Benjamin S. Glicksberg, Pratyush Tandale, Roberto Fontanez, Oommen K. Mathew, Andrew Kasarskis, Priyabrata Mukherjee, Lakshminarayanan Subramanian, Joel T. Dudley, Khader Shameer
Sepsis in the era of data-driven medicine: personalizing risks, diagnoses, treatments and prognoses. Briefings Bioinform. 21 (4) (2020)
Zicheng Hu, Benjamin S. Glicksberg, Atul J. Butte
Robust prediction of clinical outcomes using cytometry data. Bioinform. 35 (7) (2019)
Marcus A. Badgeley, John R. Zech, Luke Oakden-Rayner, Benjamin S. Glicksberg, Manway Liu, William Gale, Michael V. McConnell, Bethany Percha, Thomas M. Snyder, Joel T. Dudley
Deep learning predicts hip fracture using confounding patient and healthcare variables. npj Digit. Medicine 2 (2019)
Kipp W. Johnson, Jessica K. De Freitas, Benjamin S. Glicksberg, Jason R. Bobe, Joel T. Dudley
Evaluation of patient re-identification using laboratory test orders and mitigation via latent space variables. PSB (2019)
Marcus A. Badgeley, Manway Liu, Benjamin S. Glicksberg, Mark M. Shervey, John R. Zech, Khader Shameer, Joseph Lehar, Eric K. Oermann, Michael V. McConnell, Thomas M. Snyder, Joel T. Dudley
CANDI: an R package and Shiny app for annotating radiographs and evaluating computer-aided diagnosis. Bioinform. 35 (9) (2019)
Benjamin S. Glicksberg, Boris Oskotsky, Phyllis M. Thangaraj, Nicholas Giangreco, Marcus A. Badgeley, Kipp W. Johnson, Debajyoti Datta, Vivek A Rudrapatna, Nadav Rappoport, Mark M. Shervey, Riccardo Miotto, Theodore C. Goldstein, Eugenia Rutenberg, Remi Frazier, Nelson Lee, Sharat Israni, Rick Larsen, Bethany Percha, Li Li, Joel T. Dudley, Nicholas P. Tatonetti, Atul J. Butte
PatientExploreR: an extensible application for dynamic visualization of patient clinical history from electronic health records in the OMOP common data model. Bioinform. 35 (21) (2019)
Khader Shameer, M. Mercedes Perez-Rodriguez, Roy Bachar, Li Li, Amy Johnson, Kipp W. Johnson, Benjamin S. Glicksberg, Milo R. Smith, Ben Readhead, Joseph Scarpa, Jebakumar Jebakaran, Patricia A. Kovatch, Sabina Lim, Wayne K. Goodman, David L. Reich, Andrew Kasarskis, Nicholas P. Tatonetti, Joel T. Dudley
Pharmacological risk factors associated with hospital readmission rates in a psychiatric cohort identified using prescriptome data mining. BMC Medical Informatics Decis. Mak. 18 (S-3) (2018)
Kipp W. Johnson, Benjamin S. Glicksberg, Rachel Hodos, Khader Shameer, Joel T. Dudley
Causal inference on electronic health records to assess blood pressure treatment targets: An application of the parametric g formula. PSB (2018)
Benjamin S. Glicksberg, Riccardo Miotto, Kipp W. Johnson, Khader Shameer, Li Li, Rong Chen, Joel T. Dudley
Automated disease cohort selection using word embeddings from Electronic Health Records. PSB (2018)
Marcus A. Badgeley, John R. Zech, Luke Oakden-Rayner, Benjamin S. Glicksberg, Manway Liu, William Gale, Michael V. McConnell, Beth Percha, Thomas M. Snyder, Joel T. Dudley
Deep Learning Predicts Hip Fracture using Confounding Patient and Healthcare Variables. CoRR (2018)
Beau Norgeot, Dmytro Lituiev, Benjamin S. Glicksberg, Atul J. Butte
Time Aggregation and Model Interpretation for Deep Multivariate Longitudinal Patient Outcome Forecasting Systems in Chronic Ambulatory Care. CoRR (2018)
Milo R. Smith, Benjamin S. Glicksberg, Li Li, Rong Chen, Hirofumi Morishita, Joel T. Dudley
Loss-of-function of neuroplasticity-related genes confers risk for human neurodevelopmental disorders. PSB (2018)
Venet Osmani, Li Li, Matteo Danieletto, Benjamin S. Glicksberg, Joel Dudley, Oscar Mayora
Automatic processing of Electronic Medical Records using Deep Learning. PervasiveHealth (2018)
Khader Shameer, Benjamin S. Glicksberg, Rachel Hodos, Kipp W. Johnson, Marcus A. Badgeley, Ben Readhead, Max S. Tomlinson, Timothy O'Connor, Riccardo Miotto, Brian A. Kidd, Rong Chen, Avi Ma'ayan, Joel T. Dudley
Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning. Briefings Bioinform. 19 (4) (2018)
Venet Osmani, Li Li, Matteo Danieletto, Benjamin S. Glicksberg, Joel Dudley, Oscar Mayora
Processing of Electronic Health Records using Deep Learning: A review. CoRR (2018)
Khader Shameer, Marcus A. Badgeley, Riccardo Miotto, Benjamin S. Glicksberg, Joseph W. Morgan, Joel T. Dudley
Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams. Briefings Bioinform. 18 (1) (2017)
Zichen Wang, Li Li, Benjamin S. Glicksberg, Ariel Israel, Joel T. Dudley, Avi Ma'ayan
Predicting age by mining electronic medical records with deep learning characterizes differences between chronological and physiological age. J. Biomed. Informatics 76 (2017)
Meng Ma, Changchang Wang, Benjamin S. Glicksberg, Eric E. Schadt, Shuyu Dan Li, Rong Chen
Identify Cancer Driver Genes Through Shared Mendelian Disease Pathogenic Variants and Cancer Somatic Mutations. PSB (2017)
Benjamin S. Glicksberg, Li Li, Marcus A. Badgeley, Khader Shameer, Roman Kosoy, Noam D. Beckmann, Nam Pho, Jörg Hakenberg, Meng Ma, Kristin L. Ayers, Gabriel E. Hoffman, Shuyu Dan Li, Eric E. Schadt, Chirag J. Patel, Rong Chen, Joel T. Dudley
Comparative analyses of population-scale phenomic data in electronic medical records reveal race-specific disease networks. Bioinform. 32 (12) (2016)
Benjamin S. Glicksberg, Li Li, Wei-Yi Cheng, Khader Shameer, Jörg Hakenberg, Rafael Castellanos, Meng Ma, Lisong Shi, Hardik Shah, Joel T. Dudley, Rong Chen
An Integrative Pipeline for Multi-Modal Discovery of Disease Relationships. Pacific Symposium on Biocomputing (2015)