{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T22:43:29Z","timestamp":1779403409291,"version":"3.53.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686615","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T00:00:00Z","timestamp":1779321600000},"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":[[2026,5,21]]},"abstract":"<jats:p>Large language models (LLMs) show promise in clinical applications but face accuracy limitations in disease risk prediction, especially for rare conditions. We evaluated ChatGPT and DeepSeek against task-specific models for cholangiocarcinoma (rare) and myocardial infarction (common) prediction. Standalone LLMs underperformed specialized models, whereas collaborative prediction improved performance. Our findings suggest hybrid architectures leveraging complementary strengths of both approaches represent a promising direction for clinical AI deployment.<\/jats:p>","DOI":"10.3233\/shti260338","type":"book-chapter","created":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T22:02:11Z","timestamp":1779400931000},"source":"Crossref","is-referenced-by-count":0,"title":["Evaluation over Generalist Large Language Models and Specialised Models for Clinical Risk Prediction"],"prefix":"10.3233","author":[{"given":"Zou","family":"Lai","sequence":"first","affiliation":[{"name":"Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems, Jiaxing University, Jiaxing 314000, China"},{"name":"Sino-European Joint Lab for Health Information Processing and Applications, Jiaxing University, Jiaxing 314000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guodao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Media Computing, Hangzhou Dianzi University, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Winfried","family":"Post","sequence":"additional","affiliation":[{"name":"Dedalus Healthcare, Bonn, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fried-Michael","family":"Dahlweid","sequence":"additional","affiliation":[{"name":"Sino-European Joint Lab for Health Information Processing and Applications, Jiaxing University, Jiaxing 314000, China"},{"name":"Dedalus Healthcare, Bonn, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7112-5420","authenticated-orcid":false,"given":"Hong","family":"Sun","sequence":"additional","affiliation":[{"name":"Provincial Key Laboratory of Multimodal Perceiving and Intelligent Systems, Jiaxing University, Jiaxing 314000, China"},{"name":"Sino-European Joint Lab for Health Information Processing and Applications, Jiaxing University, Jiaxing 314000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Opening the Personal Gate between Technology and Health Care"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260338","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,21]],"date-time":"2026-05-21T22:02:22Z","timestamp":1779400942000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260338"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,21]]},"ISBN":["9781643686615"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260338","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,21]]}}}