{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T19:21:25Z","timestamp":1790796085326,"version":"4.1.0"},"reference-count":59,"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":[{"DOI":"10.13039\/100009110","name":"Natural Science Foundation of Xinjiang Uygur Autonomous Region","doi-asserted-by":"publisher","award":["2022D01C297"],"award-info":[{"award-number":["2022D01C297"]}],"id":[{"id":"10.13039\/100009110","id-type":"DOI","asserted-by":"publisher"}]}],"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>Objective<\/jats:title>\n                    <jats:p>Artificial intelligence (AI)-driven precision medicine is moving beyond standalone prediction toward individualized treatment strategies built on multimodal evidence. Yet the field's rapid, interdisciplinary growth has produced a fragmented knowledge structure, while most bibliometric syntheses remain single-database and therefore vulnerable to coverage bias and unstable thematic inference. A cross-validated, implementation-oriented knowledge map is needed to clarify how AI innovations are converging on tailored treatment pathways.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We established a dual-database cross-validation framework using the Web of Science Core Collection (WoSCC) and Scopus (2015\u20132025). After parallel screening, preprocessing, and standardized metadata\/keyword normalization, 810 WoSCC records and 999 Scopus records were analyzed independently. Science-mapping was performed across publication dynamics, collaboration networks, journal\/reference co-citation structures, keyword clustering, burst detection, and longitudinal thematic evolution, followed by explicit cross-database consistency checks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Across 1809 publications, both databases showed concordant structural patterns: the United States and China formed the central global hubs, while institution-level networks were more stable and coherent than author-level clusters, led by Harvard Medical School, Stanford University, and major Chinese universities\/academies. The field evolved in stages from feasibility and data-source expansion to multimodal\/multi-omics integration, then toward mechanism-informed interpretability and clinically oriented stratification. Recent frontiers converge on three axes: biologically grounded multimodal inference, explainable AI constrained by biological priors, and deployable decision systems integrating imaging AI, hybrid decision support, and emerging LLM-agent paradigms.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>This dual-database, cross-validated atlas delineates a robust trajectory toward clinically executable, AI-enabled personalized medicine. By linking thematic evolution to deployability and interpretability, it provides a transferable framework to prioritize patient stratification, therapy optimization, and workflow-integrated decision support in real-world settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076261436251","type":"journal-article","created":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T11:34:40Z","timestamp":1774006480000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["From algorithms to clinical execution: A cross-validated knowledge atlas of AI-enabled precision care (2015\u20132025)"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-1919-0290","authenticated-orcid":false,"given":"Boxiang","family":"Zhang","sequence":"first","affiliation":[{"name":"The Affiliated Cancer Hospital of Xinjiang Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lucy","family":"Yue Lau","sequence":"additional","affiliation":[{"name":"Harvard Medical School"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kejin","family":"Li","sequence":"additional","affiliation":[{"name":"Nanfang Hospital, Southern Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boyang","family":"Li","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Zhengzhou University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zehao","family":"Hong","sequence":"additional","affiliation":[{"name":"The First Affiliated Hospital of Zhengzhou University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard J.","family":"Aldridge","sequence":"additional","affiliation":[{"name":"University of Minnesota"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth A.","family":"Whitmore","sequence":"additional","affiliation":[{"name":"University of Minnesota"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zeliang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Gastrointestinal Surgery, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-7413-2463","authenticated-orcid":false,"given":"Yi","family":"Chen","sequence":"additional","affiliation":[{"name":"The Affiliated Cancer Hospital of Xinjiang Medical University"},{"name":"Harvard Medical School"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,3,20]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.3892\/mi.2025.289"},{"key":"e_1_3_3_3_2","first-page":"15","article-title":"Emerging biomarkers in prostate cancer diagnosis and treatment: insights into genetic, RNA and metabolic markers (review)","volume":"68","author":"Huang Y","year":"2026","unstructured":"Huang Y, Mao J, Li X. 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