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Abstract 4367840: Optimizing the Accuracy of Natural Language Processing Models for Pulmonary Embolism Detection Through Integration with Claims Data: The PE-EHR+ Study

Year: 2025

Type: conference-abstract

Source: Circulation

DOI: 10.1161/circ.152.suppl_3.4367840

Authors: SINA RASHEDI, Syed Bukhari, Darsiya Krishnathasan, Candrika Khairani, Antoine Bejjani, Mariana Pfeferman, Mehrdad Zarghami, Eric Secemsky, Farbod Rahaghi, Mohamad Hussain, HAMID MOJIBIAN, Samuel Goldhaber, Li Zhou, Richard Yang, Liqin Wang, Harlan Krumholz, Gregory Piazza, Behnood Bikdeli

Institutions: Brigham and Women's Hospital, Johns Hopkins University, Rochester General Hospital, University of Pittsburgh Medical Center, Jamaica Hospital, Beth Israel Deaconess Medical Center, Beth Israel Deaconess Hospital, Harvard University, Yale University

Language: English

Topic: Machine Learning in Healthcare

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: closed

OpenAlex ID: W4415792230

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Cited by: 1

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