{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:50Z","timestamp":1755219830429,"version":"3.43.0"},"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>Balancing operational feasibility with the performance of natural language processing (NLP) systems is a significant challenge. This study presents a hybrid strategy to integrate manually curated rules, small language model (SLM), and large language model (LLM) for cohort identification tasks. This approach demonstrates superior performance in terms of both computational efficiency and NLP validity, as shown here in two separate tasks using large number of clinical notes from the US Department of Veteran Affairs (VA) Healthcare system.<\/jats:p>","DOI":"10.3233\/shti250948","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:36:02Z","timestamp":1754566562000},"source":"Crossref","is-referenced-by-count":0,"title":["The Best of All Worlds: A Hybrid Approach to Cohort Identification with Rules, Small and Large Language Models"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6830-9544","authenticated-orcid":false,"given":"Qiwei","family":"Gan","sequence":"first","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"},{"name":"Department of Internal Medicine, University of Utah Medical School, Salt Lake"}]},{"given":"Jianlin","family":"Shi","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"},{"name":"Department of Internal Medicine, University of Utah Medical School, Salt Lake"}]},{"given":"Annie","family":"Bowles","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"},{"name":"Department of Internal Medicine, University of Utah Medical School, Salt Lake"}]},{"given":"Elizabeth","family":"Hanchrow","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"}]},{"given":"John","family":"Stanley","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"}]},{"given":"Mengke","family":"Hu","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"},{"name":"Department of Internal Medicine, University of Utah Medical School, Salt Lake"}]},{"given":"Scott L.","family":"Duvall","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"},{"name":"Department of Internal Medicine, University of Utah Medical School, Salt Lake"}]},{"given":"Patrick R.","family":"Alba","sequence":"additional","affiliation":[{"name":"VA Salt Lake City Health Care System, Salt Lake City, UT, USA"},{"name":"Department of Internal Medicine, University of Utah Medical School, Salt Lake"}]}],"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\/SHTI250948","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:36:03Z","timestamp":1754566563000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250948"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250948","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]]}}}