This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (325) Clinical Informatics (1050) Ontologies, Classifications, and Coding (243) Natural Language Processing (706) Clinical Information and Decision Making (1434) Artificial Intelligence (1421) Homelessness (31) Social Determinants of Health (36) Ethical, Legal, and Social Issues in AI (33) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (591) Electronic Health Records (1068)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63445, first published .
Using Large Language Models to Abstract Complex Social Determinants of Health From Original and Deidentified Medical Notes: Development and Validation Study

Using Large Language Models to Abstract Complex Social Determinants of Health From Original and Deidentified Medical Notes: Development and Validation Study

Using Large Language Models to Abstract Complex Social Determinants of Health From Original and Deidentified Medical Notes: Development and Validation Study

Authors of this article:

Alexandra Ralevski1, 2 Author Orcid Image ;   Nadaa Taiyab3 Author Orcid Image ;   Michael Nossal2 Author Orcid Image ;   Lindsay Mico2 Author Orcid Image ;   Samantha Piekos1 Author Orcid Image ;   Jennifer Hadlock1, 4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Alexandra Ralevski   1, 2 , PhD ;   Nadaa Taiyab   3 , MALD ;   Michael Nossal   2 , MA ;   Lindsay Mico   2 , MS ;   Samantha Piekos   1 , PhD ;   Jennifer Hadlock   1, 4 , MD

1 Institute for Systems Biology, Seattle, WA, United States

2 Providence Health & Services, Renton, WA, United States

3 Tegria, LLC, Madison, WI, United States

4 Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, United States

Corresponding Author: