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Steven Horng

Showing results (11-20 of 36) with videos related to

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Research and Practice in Thrombosis and Haemostasis|July 3, 2025
Using a transformer language model to curate a pulmonary embolism dataset from the Medical Information Mart for Intensive Care IV: MIMIC-IV-Ext-PEBarbara D Lam, Shengling Ma, Iuliia Kovalenko, et al.
Plos One|April 7, 2017
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learningSteven Horng, David A Sontag, Yoni Halpern, et al.
Proceedings of Machine Learning Research|March 25, 2026
Sample-Specific Debiasing for Better Image-Text ModelsPeiqi Wang, Yingcheng Liu, Ching-Yun Ko, et al.
Academic Emergency Medicine : Official Journal of the Society for Academic Emergency Medicine|May 6, 2017
Risk of Intracranial Hemorrhage in Ground-level Fall With Antiplatelet or Anticoagulant AgentsMichael Ganetsky, Gregory Lopez, Tara Coreanu, et al.
International Journal of Medical Informatics|April 29, 2019
Mobile device ownership among emergency department patientsEugene Kim, John Torous, Steven Horng, et al.
The Journal of Emergency Medicine|May 29, 2012
Prospective evaluation of daily performance metrics to reduce emergency department length of stay for surgical consultsSteven Horng, Lina Pezzella, Carrie D Tibbles, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 25, 2022
Multimodal Representation Learning via Maximization of Local Mutual InformationRuizhi Liao, Daniel Moyer, Miriam Cha, et al.
International Journal of Medical Informatics|October 13, 2019
Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfacesNathaniel R Greenbaum, Yacine Jernite, Yoni Halpern, et al.
Applied Clinical Informatics|June 13, 2019
Consensus Development of a Modern Ontology of Emergency Department Presenting Problems-The Hierarchical Presenting Problem Ontology (HaPPy)Steven Horng, Nathaniel R Greenbaum, Larry A Nathanson, et al.
Journal of the American Medical Informatics Association : JAMIA|May 3, 2024
Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writingSharon Jiang, Barbara D Lam, Monica Agrawal, et al.
Pageof 4

Showing results (11-20 of 36) with videos related to

Sort By:
Pageof 4
Research and Practice in Thrombosis and Haemostasis|July 3, 2025
Using a transformer language model to curate a pulmonary embolism dataset from the Medical Information Mart for Intensive Care IV: MIMIC-IV-Ext-PEBarbara D Lam, Shengling Ma, Iuliia Kovalenko, et al.
Plos One|April 7, 2017
Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learningSteven Horng, David A Sontag, Yoni Halpern, et al.
Proceedings of Machine Learning Research|March 25, 2026
Sample-Specific Debiasing for Better Image-Text ModelsPeiqi Wang, Yingcheng Liu, Ching-Yun Ko, et al.
Academic Emergency Medicine : Official Journal of the Society for Academic Emergency Medicine|May 6, 2017
Risk of Intracranial Hemorrhage in Ground-level Fall With Antiplatelet or Anticoagulant AgentsMichael Ganetsky, Gregory Lopez, Tara Coreanu, et al.
International Journal of Medical Informatics|April 29, 2019
Mobile device ownership among emergency department patientsEugene Kim, John Torous, Steven Horng, et al.
The Journal of Emergency Medicine|May 29, 2012
Prospective evaluation of daily performance metrics to reduce emergency department length of stay for surgical consultsSteven Horng, Lina Pezzella, Carrie D Tibbles, et al.
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention|October 25, 2022
Multimodal Representation Learning via Maximization of Local Mutual InformationRuizhi Liao, Daniel Moyer, Miriam Cha, et al.
International Journal of Medical Informatics|October 13, 2019
Improving documentation of presenting problems in the emergency department using a domain-specific ontology and machine learning-driven user interfacesNathaniel R Greenbaum, Yacine Jernite, Yoni Halpern, et al.
Applied Clinical Informatics|June 13, 2019
Consensus Development of a Modern Ontology of Emergency Department Presenting Problems-The Hierarchical Presenting Problem Ontology (HaPPy)Steven Horng, Nathaniel R Greenbaum, Larry A Nathanson, et al.
Journal of the American Medical Informatics Association : JAMIA|May 3, 2024
Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writingSharon Jiang, Barbara D Lam, Monica Agrawal, et al.
Pageof 4