Steven Horng
Steven Horng
Clinical Lead for Machine Learning, Beth Israel Deaconess Medical Center
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Cited by
Cited by
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
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
A Johnson, L Bulgarelli, T Pollard, S Horng, LA Celi, R Mark
PhysioNet. Available online at: https://physionet. org/content/mimiciv/1.0 …, 2020
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
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
Using anchors to estimate clinical state without labeled data
Y Halpern, Y Choi, S Horng, D Sontag
AMIA Annual Symposium Proceedings 2014, 606, 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
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
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
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
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
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
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
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
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
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
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), 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
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
Clinical tagging with joint probabilistic models
Y Halpern, S Horng, D Sontag
Machine Learning for Healthcare Conference, 209-225, 2016
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