{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T18:11:21Z","timestamp":1793211081968,"version":"4.5.0"},"reference-count":56,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Dalian Municipal Science and Technology Bureau","award":["2025ZDJH01PT107"],"award-info":[{"award-number":["2025ZDJH01PT107"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["DIGITAL HEALTH"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Large language models (LLMs) are increasingly studied for clinical decision support, but high-risk cardiology exposes persistent weaknesses in hallucination control, guideline adherence, and medication-safety reasoning. Heart failure with reduced ejection fraction (HFrEF) is a demanding test case because safe care requires structured guideline-directed therapy, comorbidity-aware monitoring, and reliable risk warnings.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed a dynamic alignment framework using 1087 retrospective HFrEF cases from Affiliated Zhongshan Hospital of Dalian University. An open-source LLaMA-3.1 backbone was optimized through four sequential stages: continual pre-training for heart-failure domain adaptation, supervised fine-tuning for structured clinical responses, reinforcement policy optimization for safety-oriented alignment, and retrieval-augmented generation for guideline grounding. Models were assessed with dual-track clinical and linguistic metrics.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>LLaMA-3.1 was the strongest supervised baseline, but supervised fine-tuning alone did not fully resolve guideline-adherence limitations. Staged alignment produced a measurable Alignment Tax: the final retrieval-grounded variant improved the Clinical Score from 0.716 to 0.864 and reached a Guideline Score of 0.881, while BLEU-4 decreased from 0.371 to 0.272. The decline in surface overlap coincided with stronger risk safety, stricter structure, and more guideline-directed outputs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Dynamic alignment shifted the model from linguistic mimicry toward clinically constrained HFrEF decision support. These findings suggest that staged optimization with policy alignment and retrieval grounding can improve evidence-based recommendations, while conventional language-overlap metrics may underestimate clinically safer generation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076261487568","type":"journal-article","created":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T17:37:40Z","timestamp":1788716260000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Dynamic alignment of large language models for evidence-grounded heart failure decision support"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-1926-0470","authenticated-orcid":false,"given":"Lu","family":"Liu","sequence":"first","affiliation":[{"name":"Dalian Medical University"},{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenchen","family":"Dong","sequence":"additional","affiliation":[{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunbo","family":"Ba","sequence":"additional","affiliation":[{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haihong","family":"Yan","sequence":"additional","affiliation":[{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxiao","family":"Tang","sequence":"additional","affiliation":[{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Sun","sequence":"additional","affiliation":[{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huilin","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Malaya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7210-8086","authenticated-orcid":false,"given":"Boyuan","family":"Shi","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qin","family":"Yu","sequence":"additional","affiliation":[{"name":"Dalian Medical University"},{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shulong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Affiliated Zhongshan Hospital of Dalian University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"e_1_3_7_2_2","doi-asserted-by":"publisher","DOI":"10.26599\/1671-5411.2025.03.002"},{"key":"e_1_3_7_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/eurheartj\/ehab368"},{"key":"e_1_3_7_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41569-024-01046-6"},{"key":"e_1_3_7_5_2","first-page":"e895","article-title":"2022 AHA\/ACC\/HFSA guideline for the management of heart failure: A report of the American college of cardiology\/american heart association joint committee on clinical practice guidelines","volume":"145","author":"Heidenreich PA","year":"2022","unstructured":"Heidenreich PA, Bozkurt B, Aguilar D, et al. 2022 AHA\/ACC\/HFSA guideline for the management of heart failure: A report of the American college of cardiology\/american heart association joint committee on clinical practice guidelines. 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