{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T09:51:37Z","timestamp":1769939497467,"version":"3.49.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Heart Failure (HF) is one of the leading causes of rehospitalization in the United States. While Social Determinants of Health (SDOH) play critical roles in health outcomes, they are often underrepresented in structured electronic health records (EHR) and hidden in unstructured clinical notes. This study leverages advanced large language models (LLM) to extract SDOHs from clinical text and uses logistic regression to analyze their association with HF readmissions. By identifying key SDOHs (e.g. tobacco usage, limited transportation) linked to readmission risk, this work also offers actionable insights for reducing readmissions and improving patient care.<\/jats:p>","DOI":"10.3233\/shti251272","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:46:48Z","timestamp":1754567208000},"source":"Crossref","is-referenced-by-count":1,"title":["Mining Social Determinants of Health for Heart Failure Patient 30-Day Readmission via Large Language Model"],"prefix":"10.3233","author":[{"given":"Mingchen","family":"Shao","sequence":"first","affiliation":[{"name":"Emory University, Atlanta, Georgia, US"}]},{"given":"Youjeong","family":"Kang","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, US"}]},{"given":"Xiao","family":"Hu","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, US"}]},{"given":"Hyunjung Gloria","family":"Kwak","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, US"}]},{"given":"Carl","family":"Yang","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, US"}]},{"given":"Jiaying","family":"Lu","sequence":"additional","affiliation":[{"name":"Emory University, Atlanta, Georgia, US"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI251272","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:46:49Z","timestamp":1754567209000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI251272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti251272","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}