{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T10:22:09Z","timestamp":1790763729005,"version":"4.1.0"},"reference-count":62,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T00:00:00Z","timestamp":1764288000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:p>China\u2019s primary care system faced persistent challenges, including uneven resource distribution, a shortage of general practitioners, and a growing burden of chronic diseases. Artificial intelligence (AI) offered new tools to address these issues. This narrative review summarized the applications, benefits, challenges, and practical recommendations for DeepSeek. Literature searches were conducted across both Chinese and English databases, including China National Knowledge Infrastructure, Wanfang Data, and PubMed. In addition, official websites of provincial Health Commissions were searched for AI policies and reports related to DeepSeek deployment. Evidence showed that DeepSeek had been applied to assist clinical decision-making, support chronic disease management, and enhance medical education and research. Reported outcomes included improved diagnostic efficiency, guideline adherence, and patient engagement. However, challenges remained, such as limited model interpretability, potential reductions in humanistic care, unequal accessibility, technical constraints, and data privacy concerns.<\/jats:p>","DOI":"10.3389\/fpubh.2025.1721308","type":"journal-article","created":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T06:29:18Z","timestamp":1764311358000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Application and challenges of DeepSeek in primary care in China"],"prefix":"10.3389","volume":"13","author":[{"given":"Jinyi","family":"Zhang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingyou","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zengxiang","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qingguo","family":"Lyu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,11,28]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"949","DOI":"10.1186\/s12909-023-04945-3","article-title":"Familiarity of teaching skills among general practitioners transfer training trainers in China: a cross-sectional 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