{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T06:07:16Z","timestamp":1788847636243,"version":"build-2803163510"},"reference-count":25,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["bjui-journals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["BJU International"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To conduct an analysis of publication trends and a systematic review of randomized controlled trials (RCTs) to characterize the current state of artificial intelligence (AI) use in genitourinary (GU) oncology, as AI has emerged as a transformative tool in healthcare with potential applications in diagnostics, treatment planning, and prognostication.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica dataBASE (EMBASE; Ovid), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) Ultimate for studies related to AI and GU oncology, excluding non\u2010English papers, non\u2010human studies, review articles, and articles using AI solely for manuscript writing. Publication trends were analysed from 2013 to 2023 and categorized by study design and cancer type. RCTs were evaluated through systematic review using Covidence (Veritas Health Innovation Ltd, Melbourne, Victoria, Australia) for screening and data extraction. Two reviewers independently assessed all studies, with risk of bias (RoB) evaluated using the Cochrane RoB 2.0 tool.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Of 2409 articles identified, 1220 met inclusion criteria. These included 962 retrospective articles, 175 prospective studies, 79 studies with combined retrospective\/prospective methods, and four RCTs. Studies most commonly addressed prostate (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009923), renal (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009274), and urothelial (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009194) cancers. Publications grew from 14 in 2013 to 362 in 2023, with substantial acceleration in 2019. Four RCTs were identified \u2013 one in urothelial cancer and three in prostate cancer. Two RCTs evaluated AI\u2010based diagnostics, demonstrating improved performance over conventional methods; the remaining two RCTs evaluated AI in prognostication and treatment planning, showing improved gains in imaging interpretation and operational efficiency. RoB varied across studies, primarily related to randomisation and deviations from intended interventions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Artificial intelligence research in GU oncology has grown, although high\u2010level evidence from RCTs remains limited. Existing trials underscore AI's promise in diagnostics, prognostication, and treatment planning, and the rapidly evolving nature of this field warrants continued prospective investigation.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/bju.70361","type":"journal-article","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T12:17:22Z","timestamp":1782476242000},"page":"549-557","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial intelligence in genitourinary oncology: publication trends and systematic review"],"prefix":"10.1111","volume":"138","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-0613-9471","authenticated-orcid":false,"given":"Alee","family":"Kim","sequence":"first","affiliation":[{"name":"The University of Oklahoma College of Medicine  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-3867-3082","authenticated-orcid":false,"given":"Nicole A.","family":"Moore","sequence":"additional","affiliation":[{"name":"The University of Oklahoma College of Medicine  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tammy","family":"Dong","sequence":"additional","affiliation":[{"name":"The University of Oklahoma College of Medicine  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kelsy","family":"Fu","sequence":"additional","affiliation":[{"name":"The University of Oklahoma College of Medicine  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katie","family":"Keyser","sequence":"additional","affiliation":[{"name":"Stephenson Cancer Center University of Oklahoma Health Sciences Center  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shari","family":"Clifton","sequence":"additional","affiliation":[{"name":"Stephenson Cancer Center University of Oklahoma Health Sciences Center  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adanma","family":"Ayanambakkam","sequence":"additional","affiliation":[{"name":"Stephenson Cancer Center University of Oklahoma Health Sciences Center  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan","family":"Nipp","sequence":"additional","affiliation":[{"name":"Stephenson Cancer Center University of Oklahoma Health Sciences Center  Oklahoma City OK USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2022.11.023"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2019.02.033"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2015.01.005"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13045-023-01511-8"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(17)33297-X"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1097\/JS9.0000000000002481"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/7842566"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.4111\/icu.20230435"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1038\/s43018-024-00756-7"},{"key":"e_1_2_8_11_1","first-page":"1","article-title":"Artificial intelligence in oncology: current capabilities, future opportunities, and ethical considerations","volume":"42","author":"Shreve JT","year":"2022","journal-title":"Am Soc Clin Oncol Educ Book"},{"key":"e_1_2_8_12_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.l4898"},{"key":"e_1_2_8_13_1","first-page":"12","article-title":"Cancer statistics","volume":"1","author":"Siegel RLGA","year":"2024","journal-title":"CA Cancer J Clin"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.brachy.2020.03.004"},{"key":"e_1_2_8_15_1","doi-asserted-by":"publisher","DOI":"10.1097\/01.ju.0000051322.60266.06"},{"key":"e_1_2_8_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euo.2019.05.002"},{"key":"e_1_2_8_17_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00345-022-04086-0"},{"key":"e_1_2_8_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-020-01191-1"},{"key":"e_1_2_8_19_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2023.5738"},{"key":"e_1_2_8_20_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2023.1227152"},{"key":"e_1_2_8_21_1","unstructured":"Intelligence SIfH\u2010CA.Artificial intelligence glossary.2024. 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