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
Yoni HalpernGoogleVerified email at google.com
Alistair JohnsonThe Hospital for Sick Children, Child Health Evaluative SciencesVerified email at sickkids.ca
Nathan ShapiroBeth Israel Deaconess MEdical CenterVerified email at bidmc.harvard.edu
Yacine JerniteResearch Scientist, HuggingFaceVerified email at cs.nyu.edu
Ruizhi (Ray) LiaoMassachusetts Institute of TechnologyVerified email at mit.edu
Polina GollandMassachusetts Institute of TechnologyVerified email at mit.edu
Jennifer P. Stevens, MDDirector, Center for Healthcare Delivery Science, Beth Israel Deaconess Medical CenterVerified email at bidmc.harvard.edu
Ashley L. O'Donoghue, PhDBeth Israel Deaconess Medical Center; Harvard Medical SchoolVerified email at bidmc.harvard.edu
Irene Y. ChenPhD Student, MITVerified email at mit.edu
Monica AgrawalPhD Student, MIT CSAILVerified email at mit.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
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
Victor Novack MD PhD, Professor of M...Head, Research Authority, Soroka University Medical Center and Ben-Gurion University of the NegevVerified email at clalit.org.il

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	414*	2019
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	264	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	195	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	131	2016
Mimic-iv (version 0.4) A Johnson, L Bulgarelli, T Pollard, S Horng, LA Celi, R Mark IV PhysioNet, 2020	104	2020
Using anchors to estimate clinical state without labeled data Y Halpern, Y Choi, S Horng, D Sontag AMIA Annual Symposium Proceedings 2014, 606, 2014	64	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	53	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	41	2017
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	41	2012
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	27	2020
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	22	2020
Mimic-cxr database A Johnson, T Pollard, R Mark, S Berkowitz, S Horng PhysioNet10 13026, C2JT1Q, 2019	21	2019
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, ... International Conference on Medical Image Computing and Computer-Assisted …, 2020	20	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	20	2013
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	19*	2019
A Model for Electronic Handoff Between the Emergency Department and Inpatient Units LD Sanchez, DT Chiu, L Nathanson, S Horng, RE Wolfe, ML Zeidel, ... The Journal of emergency medicine 53 (1), 142-150, 2017	15	2017
Clinical tagging with joint probabilistic models Y Halpern, S Horng, D Sontag Machine Learning for Healthcare Conference, 209-225, 2016	14	2016
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	12	2020
Turning the crank for machine learning: ease, at what expense? TJ Pollard, I Chen, J Wiens, S Horng, D Wong, M Ghassemi, H Mattie, ... The Lancet Digital Health 1 (5), 198-199, 2019	12	2019
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	12	2019

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