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2020 – today
- 2024
[j30]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: 102750 (2024)- [j29]Benjamin S. Glicksberg
, Prem Timsina, Dhaval Patel, Ashwin Sawant, Akhil Vaid, Ganesh Raut, Alexander W. Charney, Donald Apakama, Brendan G. Carr, Robert Freeman, Girish N. Nadkarni, Eyal Klang:
Evaluating the accuracy of a state-of-the-art large language model for prediction of admissions from the emergency room. J. Am. Medical Informatics Assoc. 31(9): 1921-1928 (2024) - [j28]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): 59 (2024) - [i13]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 abs/2401.02851 (2024) - 2023
- [j27]Zhe He, Rui Zhang, Gayo Diallo, Zhengxing Huang, Benjamin S. Glicksberg:
Editorial: Explainable artificial intelligence for critical healthcare applications. Frontiers Artif. Intell. 6 (2023) - [j26]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 A. 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): 196-207 (2023) - [j25]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 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 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): 208-219 (2023) - [j24]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) - [c17]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: 101-110 - [c16]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: 230-247 - [i12]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 abs/2311.17969 (2023) - 2022
- [j23]Faris F. Gulamali, Ashwin Sawant, Patricia H. 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) - [c15]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 - [c14]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: 9:1-9:9 - [c13]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: 11-20 - [c12]Bar H. Ezra, Shreyas Havaldar, Benjamin S. Glicksberg, Nadav Rappoport:
Multi-Dimensional Laboratory Test Score as a Proxy for Health. MIE 2022: 219-223 - [c11]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: 1789-1798 - [i11]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 abs/2212.14040 (2022) - 2021
- [j22]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): 40 (2021) - [j21]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): 329-339 (2021) - [j20]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: 742723 (2021) - [j19]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): 2716-2727 (2021) - [j18]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): 1-19 (2021) - [j17]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): 100337 (2021) - [j16]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): 100389 (2021) - [j15]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): 38-44 (2021) - [c10]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 - [c9]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 - [i10]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 abs/2101.04013 (2021) - [i9]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 abs/2104.02932 (2021) - [i8]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 abs/2104.04968 (2021) - [i7]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 J. Chalk, Guillermo M. Delgado-Aparicio, Melissa A. 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, 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 abs/2112.12554 (2021) - [i6]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 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 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 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, 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 abs/2112.12582 (2021) - 2020
- [j14]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): 1182-1195 (2020) - [j13]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): 6 (2020) - [j12]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) - [j11]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) - [j10]Fayzan F. Chaudhry, Matteo Danieletto, Eddye Golden, Jerome R. 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): 1378 (2020) - [c8]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: 14-25 - [i5]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 abs/2003.06516 (2020) - [i4]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 abs/2012.14065 (2020)
2010 – 2019
- 2019
- [j9]Zicheng Hu, Benjamin S. Glicksberg, Atul J. Butte:
Robust prediction of clinical outcomes using cytometry data. Bioinform. 35(7): 1197-1203 (2019) - [j8]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): 1610-1612 (2019) - [j7]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): 4515-4518 (2019) - [j6]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) - [c7]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: 415-426 - 2018
- [j5]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): 656-678 (2018) - [j4]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 H. 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): 79:1-79:11 (2018) - [c6]Venet Osmani, Li Li, Matteo Danieletto, Benjamin S. Glicksberg, Joel Dudley, Oscar Mayora:
Automatic processing of Electronic Medical Records using Deep Learning. PervasiveHealth 2018: 251-257 - [c5]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: 68-79 - [c4]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: 145-156 - [c3]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: 180-191 - [i3]Venet Osmani, Li Li, Matteo Danieletto, Benjamin S. Glicksberg, Joel Dudley, Oscar Mayora:
Processing of Electronic Health Records using Deep Learning: A review. CoRR abs/1804.01758 (2018) - [i2]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 abs/1811.03695 (2018) - [i1]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 abs/1811.12589 (2018) - 2017
- [j3]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): 105-124 (2017) - [j2]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: 59-68 (2017) - [c2]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: 473-484 - 2016
- [j1]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): 101-110 (2016) - 2015
- [c1]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: 407-418
Coauthor Index
Joel Dudley
aka: Joel T. Dudley
aka: Joel T. Dudley
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