{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T20:16:22Z","timestamp":1787170582164,"version":"build-2736575974"},"reference-count":20,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T00:00:00Z","timestamp":1643068800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Neurourology and Urodynamics"],"published-print":{"date-parts":[[2022,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The increasing wealth of clinical data may become unmanageable for a physician to assimilate into optimal decision\u2010making without assistance. Utilizing a novel machine learning (ML) approach, we sought to develop algorithms to predict patient outcomes following the overactive bladder treatments OnabotulinumtoxinA (OBTX\u2010A) injection and sacral neuromodulation (SNM).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>ROSETTA datasets for overactive bladder patients randomized to OBTX\u2010A or SNM were obtained. Novel ML algorithms, using reproducing kernel techniques were developed and tasked to predict outcomes including treatment response and decrease in urge urinary incontinence episodes in both the OBTX\u2010A and SNM cohorts, in validation and test sets. Blinded expert urologists also predicted outcomes. Receiver operating characteristic curves were generated and AUCs calculated for comparison to lines of ignorance and the expert urologists\u2019 predictions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Trained algorithms demonstrated outstanding accuracy in predicting treatment response (OBTX\u2010A: AUC 0.95; SNM: 0.88). Algorithms accurately predicted mean decrease in urge urinary incontinence episodes (MSE\u2009&lt;\u20090.15) in OBTX\u2010A and SNM. Algorithms were superior to human experts in response prediction for OBTX\u2010A, and noninferior to human experts in response prediction for SNM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Novel ML algorithms were accurate, superior to expert urologists in predicting OBTX\u2010A outcomes, and noninferior to expert urologists in predicting SNM outcomes. Some aspects of the physician\u2013patient interaction are subtle and uncomputable, and thus ML may complement, but not supplant, a physician's judgment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/nau.24881","type":"journal-article","created":{"date-parts":[[2022,1,25]],"date-time":"2022-01-25T15:43:35Z","timestamp":1643125415000},"page":"813-819","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Machine learning provides an accurate prognostication model for refractory overactive bladder treatment response and is noninferior to human experts"],"prefix":"10.1002","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9518-672X","authenticated-orcid":false,"given":"Glenn T.","family":"Werneburg","sequence":"first","affiliation":[{"name":"Department of Urology Glickman Urological and Kidney Institute, Cleveland Clinic Foundation  Cleveland Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric A.","family":"Werneburg","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics and Statistics Stony Brook University  Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Howard B.","family":"Goldman","sequence":"additional","affiliation":[{"name":"Department of Urology Glickman Urological and Kidney Institute, Cleveland Clinic Foundation  Cleveland Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew P.","family":"Mullhaupt","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics and Statistics Stony Brook University  Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8626-8248","authenticated-orcid":false,"given":"Sandip P.","family":"Vasavada","sequence":"additional","affiliation":[{"name":"Department of Urology Glickman Urological and Kidney Institute, Cleveland Clinic Foundation  Cleveland Ohio USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,1,25]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-010-0362-z"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASL.2013.2244083"},{"key":"e_1_2_10_4_1","unstructured":"AmodeiD AnanthanarayananS&AnubhaiRet al. 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Proceedings of the 32nd International Conference on Machine Learning Lille France. 6\u201011 July 2015."},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.3390\/s18082674"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2013.08.031"},{"key":"e_1_2_10_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.urology.2009.06.096"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2018.02.011"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.14617"},{"key":"e_1_2_10_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cct.2014.01.009"},{"key":"e_1_2_10_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.juro.2017.04.103"},{"key":"e_1_2_10_13_1","unstructured":"OglicD&G\u00e4rtnerTScalable learning in reproducing kernel Krein spaces. Proceedings of the 36th International Conference on Machine Learning Long Beach California USA. 9\u201015 June 2019."},{"key":"e_1_2_10_14_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781316219232"},{"key":"e_1_2_10_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euf.2021.07.010"},{"key":"e_1_2_10_16_1","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2019.00185"},{"key":"e_1_2_10_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euf.2020.11.001"},{"key":"e_1_2_10_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.euf.2021.04.007"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/78.485923"},{"key":"e_1_2_10_20_1","first-page":"1","volume-title":"Presented at the EAU Annual Congress Milan 2021","author":"Harding CK","year":"2021"},{"key":"e_1_2_10_21_1","doi-asserted-by":"publisher","DOI":"10.1097\/JU.0000000000000309"}],"container-title":["Neurourology and Urodynamics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/nau.24881","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/nau.24881","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/nau.24881","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,25]],"date-time":"2023-08-25T17:03:40Z","timestamp":1692983020000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/nau.24881"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,25]]},"references-count":20,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["10.1002\/nau.24881"],"URL":"https:\/\/doi.org\/10.1002\/nau.24881","archive":["Portico"],"relation":{},"ISSN":["0733-2467","1520-6777"],"issn-type":[{"value":"0733-2467","type":"print"},{"value":"1520-6777","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,25]]},"assertion":[{"value":"2021-11-08","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-01-13","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2022-01-25","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}