{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T12:16:13Z","timestamp":1787919373613,"version":"build-2784847793"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"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. Med."],"abstract":"<jats:p>Acupuncture, as an important component of traditional medicine, has been widely integrated into the management of various clinical conditions. Although acupuncture is generally considered safe and well tolerated, adverse events, including bleeding, pneumothorax, neurovascular injury, infection, and retained needles, may still occur. Current safety management approaches largely rely on operator experience and manual monitoring, which may be insufficient to address individual patient variability and dynamic procedural risks. In recent years, Artificial Intelligence (AI) has emerged as a promising technological approach to enhance patient safety management in acupuncture practice. This review focuses on the entire acupuncture care pathway and summarizes the potential applications of AI in risk identification, intelligent assistance, and safety monitoring. Current evidence suggests that AI technologies may support high-risk patient screening, personalized treatment planning, real-time procedural monitoring, and safety data management. However, existing evidence remains largely limited to technology development and preliminary validation, with insufficient clinical evidence. Future efforts should focus on establishing a human\u2013AI collaborative framework to develop comprehensive intelligent patient safety management systems, facilitating the transition of acupuncture safety management from experience-driven practices toward data-informed decision-making and proactive risk prevention.<\/jats:p>","DOI":"10.3389\/fmed.2026.1959255","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T11:16:57Z","timestamp":1787915817000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["AI\u2013enabled comprehensive patient safety management in acupuncture: from risk identification to continuous quality improvement"],"prefix":"10.3389","volume":"13","author":[{"given":"Xixi","family":"Wei","sequence":"first","affiliation":[{"name":"Heji Hospital Affiliated to Changzhi Medical College","place":["Changzhi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chao","family":"Niu","sequence":"additional","affiliation":[{"name":"Changzhi Hospital of Traditional Chinese Medicine","place":["Changzhi, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,28]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e2243665","DOI":"10.1001\/jamanetworkopen.2022.43665","article-title":"Use of acupuncture for adult health conditions, 2013 to 2021: a systematic review","volume":"5","author":"Allen","year":"2022","journal-title":"JAMA Netw Open"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"322","DOI":"10.1186\/s12906-025-05070-y","article-title":"Systematic review of clinical practice guidelines on acupuncture for chronic musculoskeletal pain","volume":"25","author":"Ho","year":"2025","journal-title":"BMC Complement Med 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