{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T04:36:25Z","timestamp":1787027785859,"version":"build-2736575974"},"reference-count":71,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T00:00:00Z","timestamp":1656201600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Cancers"],"abstract":"<jats:p>Background: Prognostication is essential to determine the risk profile of patients with urologic cancers. Methods: We utilized the SEER national cancer registry database with approximately 2 million patients diagnosed with urologic cancers (penile, testicular, prostate, bladder, ureter, and kidney). The cohort was randomly divided into the development set (90%) and the out-held test set (10%). Modeling algorithms and clinically relevant parameters were utilized for cancer-specific mortality prognosis. The model fitness for the survival estimation was assessed using the differences between the predicted and observed Kaplan\u2013Meier estimates on the out-held test set. The overall concordance index (c-index) score estimated the discriminative accuracy of the survival model on the test set. A simulation study assessed the estimated minimum follow-up duration and time points with the risk stability. Results: We achieved a well-calibrated prognostic model with an overall c-index score of 0.800 (95% CI: 0.795\u20130.805) on the representative out-held test set. The simulation study revealed that the suggestions for the follow-up duration covered the minimum duration and differed by the tumor dissemination stages and affected organs. Time points with a high likelihood for risk stability were identifiable. Conclusions: A personalized temporal survival estimation is feasible using artificial intelligence and has potential application in clinical settings, including surveillance management.<\/jats:p>","DOI":"10.3390\/cancers14133135","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T09:00:13Z","timestamp":1656234013000},"page":"3135","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Artificial Intelligence-Based Prognostic Model for Urologic Cancers: A SEER-Based Study"],"prefix":"10.3390","volume":"14","author":[{"given":"Okyaz","family":"Eminaga","sequence":"first","affiliation":[{"name":"Department of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5410-6412","authenticated-orcid":false,"given":"Eugene","family":"Shkolyar","sequence":"additional","affiliation":[{"name":"Department of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2891-5558","authenticated-orcid":false,"given":"Bernhard","family":"Breil","sequence":"additional","affiliation":[{"name":"Faculty of Health Care, Hochschule Niederrhein, University of Applied Sciences, 47805 Krefeld, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Axel","family":"Semjonow","sequence":"additional","affiliation":[{"name":"Prostate Center, Department of Urology, University Hospital Muenster, 48149 Muenster, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2569-4446","authenticated-orcid":false,"given":"Martin","family":"Boegemann","sequence":"additional","affiliation":[{"name":"Prostate Center, Department of Urology, University Hospital Muenster, 48149 Muenster, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Xing","sequence":"additional","affiliation":[{"name":"Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ilker","family":"Tinay","sequence":"additional","affiliation":[{"name":"Department of Urology, Marmara University School of Medicine, Istanbul 34854, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph C.","family":"Liao","sequence":"additional","affiliation":[{"name":"Department of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J. 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