{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T14:00:40Z","timestamp":1785074440636,"version":"3.55.0"},"reference-count":30,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T00:00:00Z","timestamp":1784764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"the General Project of Jiangsu Provincial Administration of Traditional Chinese Medicine","award":["Subject number: MS2025011"],"award-info":[{"award-number":["Subject number: MS2025011"]}]},{"name":"Nanjing University of Traditional Chinese Medicine","award":["Subject number: LCZBYJYZZ2025-004"],"award-info":[{"award-number":["Subject number: LCZBYJYZZ2025-004"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Technology and Health Care"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Artificial intelligence (AI) has generated rapidly growing research in breast cancer diagnosis and treatment, yet its intellectual structure, collaboration patterns, and thematic evolution remain unmapped.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To analyze the global research landscape of AI in breast cancer from 2001 to 2025, identifying publication trends, contributors, collaboration networks, thematic clusters, and translational gaps.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A bibliometric analysis of 7673 Web of Science articles. VOSviewer was used for co-authorship networks and keyword co-occurrence with overlay visualization; CiteSpace for burst detection.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The field grew exponentially (29.20% annual growth), with 88.41% of publications from 2020\u20132025. China (31.63%) and the United States (21.10%) dominated output, but co-authorship networks revealed limited international collaboration for China (22.4% non-Chinese co-authors) and structural exclusion of low- and middle-income countries. Seven keyword clusters showed persistent separation between technology-centric and clinically oriented terms. Temporal overlay revealed a shift from computer-aided detection (pre-2015) to deep learning (2015\u20132022) and explainable AI, federated learning, and vision transformers (2022\u20132025). Burst detection confirmed \u201cfeature selection\u201d (strength=19.53) and \u201ccomputer aided detection\u201d (strength=20.24) as historical hotspots; limited recent bursts indicate emerging frontiers are still accumulating citation impact.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI research in breast cancer has expanded rapidly with evolving themes, yet a translational gap persists between innovation and clinical integration. Future efforts should prioritize prospective validation, international collaboration with underrepresented regions, and standardized frameworks for integrating explainable and privacy-preserving AI into workflows.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/09287329261466487","type":"journal-article","created":{"date-parts":[[2026,7,23]],"date-time":"2026-07-23T13:51:29Z","timestamp":1784814689000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Mapping the knowledge landscape and research trends of artificial intelligence in breast cancer diagnosis and treatment: A bibliometric analysis"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7441-373X","authenticated-orcid":false,"given":"Cong","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China"},{"name":"Nanjing University of Chinese Medicine, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4284-4824","authenticated-orcid":false,"given":"Ke","family":"Hong","sequence":"additional","affiliation":[{"name":"Department of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-9655-0182","authenticated-orcid":false,"given":"Yu","family":"Ying","sequence":"additional","affiliation":[{"name":"Department of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China"},{"name":"Nanjing University of Chinese Medicine, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanlei","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China"},{"name":"Nanjing University of Chinese Medicine, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7368-9476","authenticated-orcid":false,"given":"Chang","family":"Yao","sequence":"additional","affiliation":[{"name":"Department of Breast Surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China"},{"name":"Nanjing University of Chinese Medicine, Nanjing 210023, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,7,23]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2023.25057"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21834"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1799-6"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.14585"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-019-0508-1"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.csbj.2014.11.005"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbusres.2021.04.070"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.21315\/eimj2025.17.3.1"},{"key":"e_1_3_3_10_2","first-page":"931245","article-title":"Mapping the knowledge structure and research trends of precision medicine in oncology: a bibliometric analysis","volume":"12","author":"Wang X","year":"2022","unstructured":"Wang X, Chen Y, Yang N, et\u00a0al. 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