{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,28]],"date-time":"2026-10-28T18:11:23Z","timestamp":1793211083772,"version":"4.5.0"},"reference-count":36,"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":"National High-Level Hospital Clinical Research Funding","award":["2022-PUMCH-C-049"],"award-info":[{"award-number":["2022-PUMCH-C-049"]}]},{"name":"National High-Level Hospital Clinical Research Funding","award":["2022-PUMCH-B-067"],"award-info":[{"award-number":["2022-PUMCH-B-067"]}]},{"name":"CAMS Innovation Fund for Medical Sciences","award":["2021-I2M-1-051"],"award-info":[{"award-number":["2021-I2M-1-051"]}]},{"name":"Beijing Students\u2019","award":["2025dcxm165"],"award-info":[{"award-number":["2025dcxm165"]}]},{"name":"Beijing Natural Science Foundation","award":["7262093"],"award-info":[{"award-number":["7262093"]}]},{"name":"Youth Fund of the National Natural Science Foundation of China","award":["82001900"],"award-info":[{"award-number":["82001900"]}]}],"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>The integration of Large Language Models (LLMs) into cancer research has progressed rapidly, but a comprehensive understanding of global trends, key contributors, and emerging research areas remains lacking. This gap hinders a comprehensive understanding of the development landscape for LLM applications in clinical oncology.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A bibliometric analysis was conducted using publications retrieved from the Web of Science Core Collection on March 15, 2026. Eligible studies were limited to English-language articles and reviews published till 2025. Records unrelated to LLMs or cancer, duplicates, retracted publications, and those missing complete metadata were excluded. A total of 896 publications were analyzed using VOSviewer, CiteSpace, and R. ClinicalTrials.gov was searched with the same term, obtaining 29 eligible trials.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Publication output increased sharply from 2022 to 2025. The USA and China dominated global output, with Germany demonstrating disproportionate citation efficiency relative to volume, and Heidelberg University and Harvard University leading institutionally. Research hotspots converged on LLM benchmarking, domain-specific fine-tuning, multi-omics integration, and perioperative applications. Among 29 registered trials, application areas spanned patient communication, shared decision-making, and care equity outcomes, reflecting a transition from proof-of-concept toward randomized evaluation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>LLM-driven oncology research has expanded rapidly but remains geographically and institutionally concentrated, with prospective multicenter validation still scarce. Research is transitioning from foundational benchmarking toward fine-tuning, multimodal integration, and clinical deployment. Strengthening cross-institutional collaboration, diversifying trial populations, and developing standardized safety evaluation frameworks are essential for translating bibliometric growth into meaningful advances in cancer diagnosis, treatment, and patient outcomes.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/20552076261458966","type":"journal-article","created":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T12:04:39Z","timestamp":1780488279000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Global trends and emerging frontiers of large language models in cancer research"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-3618-9054","authenticated-orcid":false,"given":"Dianzhe","family":"Tian","sequence":"first","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhixuan","family":"Xie","sequence":"additional","affiliation":[{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"},{"name":"Chinese Academy of Medical Sciences"},{"name":"Peking Union Medical College Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zixuan","family":"Hu","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zuyi","family":"Yang","sequence":"additional","affiliation":[{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"},{"name":"Chinese Academy of Medical Sciences"},{"name":"Peking Union Medical College Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8686-7390","authenticated-orcid":false,"given":"Hu","family":"Tian","sequence":"additional","affiliation":[{"name":"Taizhou Affiliated Hospital of Nanjing University of Chinese Medicine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youxin","family":"Chen","sequence":"additional","affiliation":[{"name":"Chinese Academy of Medical Sciences"},{"name":"Peking Union Medical College Hospital"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haitao","family":"Zhao","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shunda","family":"Du","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengdan","family":"Wang","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyao","family":"Xu","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1036-3369","authenticated-orcid":false,"given":"Xin","family":"Lu","sequence":"additional","affiliation":[{"name":"Peking Union Medical College Hospital"},{"name":"Chinese Academy of Medical Sciences and Peking Union Medical College"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,3]]},"reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(25)01635-6"},{"key":"e_1_3_6_3_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-27358-6"},{"key":"e_1_3_6_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-025-01869-8"},{"key":"e_1_3_6_5_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-025-18759-4"},{"issue":"2","key":"e_1_3_6_6_2","first-page":"e251844","article-title":"A Prospective Controlled Trial of Large Language Model-based Simplification of Oncologic CT Reports for Patients with Cancer","volume":"317","author":"Prucker P","year":"2025","unstructured":"Prucker P, Bressem KK, Peeken J, et al. 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