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Steven Horng
Steven Horng
Clinical Lead for Machine Learning, Beth Israel Deaconess Medical Center
Verified email at bidmc.harvard.edu
Title
Cited by
Cited by
Year
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
2642017
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
1952017
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
1312016
Mimic-iv (version 0.4)
A Johnson, L Bulgarelli, T Pollard, S Horng, LA Celi, R Mark IV
PhysioNet, 2020
1042020
Using anchors to estimate clinical state without labeled data
Y Halpern, Y Choi, S Horng, D Sontag
AMIA Annual Symposium Proceedings 2014, 606, 2014
642014
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
532012
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
412017
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
412012
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
272020
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
222020
Mimic-cxr database
A Johnson, T Pollard, R Mark, S Berkowitz, S Horng
PhysioNet10 13026, C2JT1Q, 2019
212019
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
202020
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
202013
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
152017
Clinical tagging with joint probabilistic models
Y Halpern, S Horng, D Sontag
Machine Learning for Healthcare Conference, 209-225, 2016
142016
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
122020
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
122019
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
122019
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