Steven Horng

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David SontagProfessor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Larry NathansonAssistant Professor of Emergency Medicine, Harvard Medical SchoolVerified email at bidmc.harvard.edu
Alistair JohnsonThe Hospital for Sick Children, Child Health Evaluative SciencesVerified email at sickkids.ca
Yoni HalpernGoogleVerified email at google.com
Nathan ShapiroBeth Israel Deaconess MEdical CenterVerified email at bidmc.harvard.edu
Polina GollandMassachusetts Institute of TechnologyVerified email at mit.edu
Ruizhi (Ray) LiaoMassachusetts Institute of TechnologyVerified email at mit.edu
Yacine JerniteResearch Scientist, HuggingFaceVerified email at cs.nyu.edu
Jennifer P. Stevens, MDDirector, Center for Healthcare Delivery Science. Beth Israel Deaconess Medical CenterVerified email at bidmc.harvard.edu
Monica AgrawalPhD Student, MIT CSAILVerified email at mit.edu
Ashley L. O'Donoghue, PhDBeth Israel Deaconess Medical Center & Harvard Medical SchoolVerified email at bidmc.harvard.edu
Irene Y. ChenAssistant Professor, UC Berkeley and UCSFVerified email at berkeley.edu
David ChiuBeth Israel Deaconess Medical Center, Harvard Medical SchoolVerified email at bidmc.harvard.edu
Foster Goss, DO, MMSc, FACEPAssociate Professor, University of ColoradoVerified email at ucdenver.edu
Richard E WolfeAssociate Professor, HarvardVerified email at caregroup.org
Carrie TibblesBeth Israel Deaconess Medical Center, Boston MAVerified email at hfchaiti.org
Leon D. SanchezBW Faulkner/Harvard Medical SchoolVerified email at bwh.harvard.edu
Jonathan RubinResearch Scientist, Amazon Alexa AIVerified email at amazon.com
Charles SafranProfessor of Medicine, Harvard Medical SchoolVerified email at bidmc.harvard.edu
Michael Ganetsky, MDAssistant Professor of Emergency Medicine, Harvard Medical SchoolVerified email at bidmc.harvard.edu

Steven Horng

Clinical Lead for Machine Learning, Beth Israel Deaconess Medical Center

Verified email at bidmc.harvard.edu

Emergency Medicine Clinical Informatics Machine Learning


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MIMIC-CXR, a de-identified publicly available database of chest radiographs with free-text reports AEW Johnson, TJ Pollard, SJ Berkowitz, NR Greenbaum, MP Lungren, ... Scientific Data, 2019	837*	2019
MIMIC-IV, a freely accessible electronic health record dataset AEW Johnson, L Bulgarelli, L Shen, A Gayles, A Shammout, S Horng, ... Scientific data 10 (1), 1, 2023	432*	2023
Learning a health knowledge graph from electronic medical records M Rotmensch, Y Halpern, A Tlimat, S Horng, D Sontag Scientific reports 7 (1), 1-11, 2017	373	2017
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning S Horng, DA Sontag, Y Halpern, Y Jernite, NI Shapiro, LA Nathanson PloS one 12 (4), e0174708, 2017	244	2017
Electronic medical record phenotyping using the anchor and learn framework Y Halpern, S Horng, Y Choi, D Sontag Journal of the American Medical Informatics Association 23 (4), 731-740, 2016	154	2016
Using anchors to estimate clinical state without labeled data Y Halpern, Y Choi, S Horng, D Sontag AMIA Annual Symposium Proceedings 2014, 606, 2014	70	2014
Prospective pilot study of a tablet computer in an Emergency Department S Horng, FR Goss, RS Chen, LA Nathanson International journal of medical informatics 81 (5), 314-319, 2012	56	2012
Risk of Intracranial Hemorrhage in Ground‐level Fall With Antiplatelet or Anticoagulant Agents M Ganetsky, G Lopez, T Coreanu, V Novack, S Horng, NI Shapiro, ... Academic emergency medicine 24 (10), 1258-1266, 2017	52	2017
Robustly Extracting Medical Knowledge from EHRs: A Case Study of Learning a Health Knowledge Graph IY Chen, M Agrawal, S Horng, D Sontag Pac Symp Biocomput 25, 19-30, 2020	45	2020
A comparison of dimensionality reduction techniques for unstructured clinical text Y Halpern, S Horng, LA Nathanson, NI Shapiro, D Sontag Icml 2012 workshop on clinical data analysis 6, 2012	43	2012
Predicting Intensive Care Unit admission among patients presenting to the emergency department using machine learning and natural language processing M Fernandes, R Mendes, SM Vieira, F Leite, C Palos, A Johnson, ... PloS one 15 (3), e0229331, 2020	41	2020
Joint modeling of chest radiographs and radiology reports for pulmonary edema assessment G Chauhan, R Liao, W Wells, J Andreas, X Wang, S Berkowitz, S Horng, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020	37	2020
Improving Documentation of Presenting Problems in the Emergency Department using a Domain-specific Ontology and Machine Learning-Driven User Interfaces NR Greenbaum, Y Jernite, Y Halpern, S Calder, LA Nathanson, D Sontag, ... International Journal of Medical Informatics, 103981, 2019	32*	2019
Development and validation of a pancreatic cancer risk model for the general population using electronic health records: An observational study L Appelbaum, JP Cambronero, JP Stevens, S Horng, K Pollick, G Silva, ... European Journal of Cancer 143, 19-30, 2021	24	2021
Multimodal representation learning via maximization of local mutual information R Liao, D Moyer, M Cha, K Quigley, S Berkowitz, S Horng, P Golland, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021	23	2021
Risk of mortality and cardiopulmonary arrest in critical patients presenting to the emergency department using machine learning and natural language processing M Fernandes, R Mendes, SM Vieira, F Leite, C Palos, A Johnson, ... PloS one 15 (4), e0230876, 2020	22	2020
Predicting chief complaints at triage time in the emergency department Y Jernite, Y Halpern, S Horng, D Sontag NIPS 2013 Workshop on Machine Learning for Clinical Data Analysis and Healthcare, 2013	22	2013
Deep learning to quantify pulmonary edema in chest radiographs S Horng, R Liao, X Wang, S Dalal, P Golland, SJ Berkowitz Radiology: Artificial Intelligence 3 (2), e190228, 2021	21	2021
Fast, Structured Clinical Documentation via Contextual Autocomplete D Gopinath, M Agrawal, L Murray, S Horng, D Karger, D Sontag Machine Learning for Healthcare Conference, 842-870, 2020	18	2020
Semi-supervised Learning for Quantification of Pulmonary Edema in Chest X-Ray Images R Liao, J Rubin, G Lam, S Berkowitz, S Dalal, W Wells, S Horng, ... arXiv preprint arXiv:1902.10785, 2019	18	2019

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