{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T11:39:24Z","timestamp":1789472364796,"version":"build-2803163510"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T00:00:00Z","timestamp":1755561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Prostate Cancer Prostatic Dis"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1038\/s41391-025-01015-1","type":"journal-article","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T16:52:44Z","timestamp":1755622364000},"page":"175-180","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Machine learning models to predict postoperative incontinence after endoscopic enucleation of the prostate for benign prostatic hyperplasia: An EAU-Endourology study"],"prefix":"10.1038","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8194-0800","authenticated-orcid":false,"given":"Khi Yung","family":"Fong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3740-7141","authenticated-orcid":false,"given":"Vineet","family":"Gauhar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas R. W.","family":"Herrmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlotta","family":"Nedbal","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7169-2209","authenticated-orcid":false,"given":"Dmitry","family":"Enikeev","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9361-2342","authenticated-orcid":false,"given":"Jeremy Yuen-Chun","family":"Teoh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sarvajit","family":"Biligere","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9956-1558","authenticated-orcid":false,"given":"Steffi Kar Kei","family":"Yuen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7354-9190","authenticated-orcid":false,"given":"Daniele","family":"Castellani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6248-6478","authenticated-orcid":false,"given":"Bhaskar Kumar","family":"Somani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick","family":"Julieb\u00f8-Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6258-3286","authenticated-orcid":false,"given":"Valerie Huei Li","family":"Gan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1512-3356","authenticated-orcid":false,"given":"Edwin Jonathan","family":"Aslim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ee Jean","family":"Lim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,19]]},"reference":[{"key":"1015_CR1","doi-asserted-by":"publisher","first-page":"1579","DOI":"10.1016\/S0140-6736(20)30226-9","volume":"395","author":"N Schwalbe","year":"2020","unstructured":"Schwalbe N, Wahl B. Artificial intelligence and the future of global health. Lancet. 2020;395:1579\u201386.","journal-title":"Lancet"},{"key":"1015_CR2","doi-asserted-by":"publisher","first-page":"m689","DOI":"10.1136\/bmj.m689","volume":"368","author":"M Nagendran","year":"2020","unstructured":"Nagendran M, Chen Y, Lovejoy CA, Gordon AC, Komorowski M, Harvey H, et al. Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies. BMJ. 2020;368:m689.","journal-title":"BMJ"},{"key":"1015_CR3","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1111\/bju.14852","volume":"124","author":"J Chen","year":"2019","unstructured":"Chen J, Remulla D, Nguyen JH, Dua A, Liu Y, Dasgupta P, et al. Current status of artificial intelligence applications in urology and their potential to influence clinical practice. BJU Int. 2019;124:567\u201377.","journal-title":"BJU Int"},{"key":"1015_CR4","doi-asserted-by":"publisher","first-page":"S27","DOI":"10.5152\/tud.2020.20117","volume":"46","author":"M Shah","year":"2020","unstructured":"Shah M, Naik N, Somani BK, Hameed BMZ. Artificial intelligence (AI) in urology-Current use and future directions: An iTRUE study. Turk J Urol. 2020;46:S27\u2013s39.","journal-title":"Turk J Urol"},{"key":"1015_CR5","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1007\/s00345-025-05583-8","volume":"43","author":"J Li","year":"2025","unstructured":"Li J, Chong TW, Fong KY, Han BLJ, Tan SY, Mui JTS, et al. Will artificial intelligence (AI) replace cytopathologists: a scoping review of current applications and evidence of A.I. in urine cytology. World J Urol. 2025;43:200.","journal-title":"World J Urol"},{"key":"1015_CR6","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1007\/s00345-024-05314-5","volume":"42","author":"D Castellani","year":"2024","unstructured":"Castellani D, De Stefano V, Brocca C, Mazzon G, Celia A, Bosio A, et al. The infection post flexible UreteroreNoscopy (I-FUN) predictive model based on machine learning: a new clinical tool to assess the risk of sepsis post retrograde intrarenal surgery for kidney stone disease. World J Urol. 2024;42:612.","journal-title":"World J Urol"},{"key":"1015_CR7","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1016\/j.urology.2021.04.004","volume":"154","author":"G Magistro","year":"2021","unstructured":"Magistro G, Schott M, Keller P, Tamalunas A, Atzler M, Stief CG, et al. Enucleation vs. Resection: A Matched-pair Analysis of TURP, HoLEP and Bipolar TUEP in Medium-sized Prostates. Urology. 2021;154:221\u20136.","journal-title":"Urology"},{"key":"1015_CR8","doi-asserted-by":"publisher","first-page":"1331","DOI":"10.1089\/end.2022.0222","volume":"36","author":"D Castellani","year":"2022","unstructured":"Castellani D, Rubilotta E, Fabiani A, Maggi M, Wroclawski ML, Teoh JY-C, et al. Correlation Between Transurethral Interventions and Their Influence on Type and Duration of Postoperative Urinary Incontinence: Results from a Systematic Review and Meta-Analysis of Comparative Studies. J Endourol. 2022;36:1331\u201347.","journal-title":"J Endourol"},{"key":"1015_CR9","doi-asserted-by":"publisher","first-page":"2731","DOI":"10.1007\/s00345-022-04174-1","volume":"40","author":"M Hout","year":"2022","unstructured":"Hout M, Gurayah A, Arbelaez MCS, Blachman-Braun R, Shah K, Herrmann TRW, et al. Incidence and risk factors for postoperative urinary incontinence after various prostate enucleation procedures: systemic review and meta-analysis of PubMed literature from 2000 to 2021. World J Urol. 2022;40:2731\u201345.","journal-title":"World J Urol"},{"key":"1015_CR10","doi-asserted-by":"publisher","first-page":"180","DOI":"10.1007\/s00345-024-04886-6","volume":"42","author":"V Gauhar","year":"2024","unstructured":"Gauhar V, Castellani D, Herrmann TRW, G\u00f6kce MI, Fong KY, Gadzhiev N, et al. Incidence of complications and urinary incontinence following endoscopic enucleation of the prostate in men with a prostate volume of 80 ml and above: results from a multicenter, real-world experience of 2512 patients. World J Urol. 2024;42:180.","journal-title":"World J Urol"},{"key":"1015_CR11","doi-asserted-by":"publisher","first-page":"3033","DOI":"10.1007\/s00345-023-04626-2","volume":"41","author":"V Gauhar","year":"2023","unstructured":"Gauhar V, G\u00f3mez Sancha F, Enikeev D, Sofer M, Fong KY, Rodr\u00edguez Socarr\u00e1s M, et al. Results from a global multicenter registry of 6193 patients to refine endoscopic anatomical enucleation of the prostate (REAP) by evaluating trends and outcomes and nuances of prostate enucleation in a real-world setting. World J Urol. 2023;41:3033\u201340.","journal-title":"World J Urol"},{"key":"1015_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10462-009-9124-7","volume":"33","author":"L Rokach","year":"2010","unstructured":"Rokach L. Ensemble-based classifiers. Artificial Intell Rev. 2010;33:1\u201339.","journal-title":"Artificial Intell Rev"},{"key":"1015_CR13","doi-asserted-by":"publisher","first-page":"e0279540","DOI":"10.1371\/journal.pone.0279540","volume":"18","author":"B Langenberger","year":"2023","unstructured":"Langenberger B, Schulte T, Groene O. The application of machine learning to predict high-cost patients: A performance-comparison of different models using healthcare claims data. PLoS ONE. 2023;18:e0279540.","journal-title":"PLoS ONE"},{"key":"1015_CR14","doi-asserted-by":"publisher","DOI":"10.1177\/2325967120953404","volume":"8","author":"BC Luu","year":"2020","unstructured":"Luu BC, Wright AL, Haeberle HS, Karnuta JM, Schickendantz MS, Makhni EC, et al. Machine Learning Outperforms Logistic Regression Analysis to Predict Next-Season NHL Player Injury: An Analysis of 2322 Players From 2007 to 2017. Orthop J Sports Med. 2020;8:2325967120953404.","journal-title":"Orthop J Sports Med"},{"key":"1015_CR15","doi-asserted-by":"publisher","first-page":"2022","DOI":"10.3389\/fcimb.2022.819267","volume":"12","author":"W Hong","year":"2022","unstructured":"Hong W, Zhou X, Jin S, Lu Y, Pan J, Lin Q, et al. A Comparison of XGBoost, Random Forest, and Nomograph for the Prediction of Disease Severity in Patients With COVID-19 Pneumonia: Implications of Cytokine and Immune Cell Profile. Frontiers Cell Infect Microbiol. 2022;12:2022.","journal-title":"Frontiers Cell Infect Microbiol"},{"key":"1015_CR16","doi-asserted-by":"publisher","DOI":"10.1186\/1472-6947-11-51","volume":"11","author":"M Khalilia","year":"2011","unstructured":"Khalilia M, Chakraborty S, Popescu M. Predicting disease risks from highly imbalanced data using random forest. BMC Med Inform Decis Mak. 2011;11:51.","journal-title":"BMC Med Inform Decis Mak"},{"key":"1015_CR17","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1007\/s00345-020-03169-0","volume":"39","author":"V Houssin","year":"2021","unstructured":"Houssin V, Olivier J, Brenier M, Pierache A, Laniado M, Mouton M, et al. Predictive factors of urinary incontinence after holmium laser enucleation of the prostate: a multicentric evaluation. World J Urol. 2021;39:143\u20138.","journal-title":"World J Urol"},{"key":"1015_CR18","doi-asserted-by":"publisher","first-page":"213","DOI":"10.1016\/j.urology.2018.11.032","volume":"124","author":"LB Cornwell","year":"2019","unstructured":"Cornwell LB, Smith GE, Paonessa JE. Predictors of Postoperative Urinary Incontinence After Holmium Laser Enucleation of the Prostate: 12 Months Follow-Up. Urology. 2019;124:213\u20137.","journal-title":"Urology"},{"key":"1015_CR19","doi-asserted-by":"publisher","first-page":"e2110703-e","DOI":"10.1001\/jamanetworkopen.2021.10703","volume":"4","author":"J Herrin","year":"2021","unstructured":"Herrin J, Abraham NS, Yao X, Noseworthy PA, Inselman J, Shah ND, et al. Comparative effectiveness of machine learning approaches for predicting gastrointestinal bleeds in patients receiving antithrombotic treatment. JAMA Netw Open. 2021;4:e2110703-e.","journal-title":"JAMA Netw Open"},{"key":"1015_CR20","doi-asserted-by":"publisher","first-page":"e2110738-e","DOI":"10.1001\/jamanetworkopen.2021.10738","volume":"4","author":"F Wang","year":"2021","unstructured":"Wang F. Machine learning for predicting rare clinical outcomes\u2014finding needles in a haystack. JAMA Netw Open. 2021;4:e2110738-e.","journal-title":"JAMA Netw Open"},{"key":"1015_CR21","doi-asserted-by":"publisher","first-page":"84486","DOI":"10.1109\/ACCESS.2022.3197671","volume":"10","author":"D Saraswat","year":"2022","unstructured":"Saraswat D, Bhattacharya P, Verma A, Prasad VK, Tanwar S, Sharma G, et al. Explainable AI for Healthcare 5.0: Opportunities and Challenges. IEEE Access. 2022;10:84486\u2013517.","journal-title":"IEEE Access"}],"container-title":["Prostate Cancer and Prostatic Diseases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41391-025-01015-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41391-025-01015-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41391-025-01015-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T20:03:55Z","timestamp":1771272235000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41391-025-01015-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,19]]},"references-count":21,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["1015"],"URL":"https:\/\/doi.org\/10.1038\/s41391-025-01015-1","relation":{},"ISSN":["1365-7852","1476-5608"],"issn-type":[{"value":"1365-7852","type":"print"},{"value":"1476-5608","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,19]]},"assertion":[{"value":"25 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 August 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"(a) All methods were performed in accordance with the relevant guidelines and regulations. (b) Approval has been obtained from a named ethics committee: Asian Institute of Nephrology and Urology, AINU #11\/2022. (c) Informed consent was obtained from all participants.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}