{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T07:04:13Z","timestamp":1773644653917,"version":"3.50.1"},"reference-count":23,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T00:00:00Z","timestamp":1765238400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T00:00:00Z","timestamp":1765238400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Journal of Surgical Oncology"],"published-print":{"date-parts":[[2026,2]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background and Objectives<\/jats:title>\n                    <jats:p>Postoperative Ileus (POI) is a common complication after Radical Cystectomy (RC) that delays recovery and extends hospital stay. Our objective was to develop machine learning (ML) models that can predict patients at a high risk of developing POI after RC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data of patients who underwent RC for bladder cancer at our institution were retrospectively extracted for analysis and model creation. Data pre\u2010processing and variable selection were applied. Several ML models were developed, evaluated, and compared using the area under the curve (AUC), F1 score, precision, sensitivity, and specificity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Three hundred and seven patients were included in the analysis, and of these, 30 patients (9.8%) developed POI. Overall, 78.2% of patients were male and 91.2% were White. Of the various ML models, logistic regression demonstrated the highest AUC (0.98), followed by random forest (0.97), Support Vector Machine (0.97), XGBoost (0.95), simple neural network (0.87), and decision tree (0.84). Furthermore, the first two models also displayed higher specificity (0.94 and 0.93) and F1 scores (0.78 and 0.75). All models except for the decision tree and neural network achieved 100% sensitivity. Features such as age, body mass index (BMI), American Society of Anaesthesiologists (ASA) class status, surgical approach, potassium level, and the placement of a nasogastric tube were identified as key predictors of the outcome.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Based on our data, ML models can effectively predict POI after RC, especially with logistic regression and random forest. The identification of relevant predictors may contribute meaningfully to potential applications in risk stratification and personalized care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jso.70161","type":"journal-article","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T14:11:02Z","timestamp":1765289462000},"page":"226-232","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Development of a Multivariable Machine Learning Model for the Prediction of Postoperative Ileus After Radical Cystectomy"],"prefix":"10.1002","volume":"133","author":[{"given":"Murugesan","family":"Manoharan","sequence":"first","affiliation":[{"name":"Miami Cancer Institute Baptist Health South Florida Miami Florida USA"},{"name":"Herbert Wertheim College of Medicine Florida International University Miami Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0486-0334","authenticated-orcid":false,"given":"Mohamed Javid","family":"Raja Iyub","sequence":"additional","affiliation":[{"name":"Miami Cancer Institute Baptist Health South Florida Miami Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanjia","family":"Zhang","sequence":"additional","affiliation":[{"name":"AI and ML Department Baptist Health South Florida Miami Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pushan","family":"Prabhakar","sequence":"additional","affiliation":[{"name":"Miami Cancer Institute Baptist Health South Florida Miami Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arjun","family":"Pon Avudaiappan","sequence":"additional","affiliation":[{"name":"Miami Cancer Institute Baptist Health South Florida Miami Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahmoud","family":"Eldefrawy","sequence":"additional","affiliation":[{"name":"Midwestern State University Wichita Falls Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sai Raghavendra","family":"Sridhar","sequence":"additional","affiliation":[{"name":"The University of Texas at Dallas Richardson Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deerush Kannan","family":"Sakthivel","sequence":"additional","affiliation":[{"name":"Miami Cancer Institute Baptist Health South Florida Miami Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2025,12,9]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s13193-020-01226-z"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eururo.2012.11.051"},{"issue":"2","key":"e_1_2_11_4_1","first-page":"33","article-title":"Defining Postoperative Ileus and Associated Risk Factors in Patients Undergoing Radical Cystectomy With an Enhanced Recovery After Surgery (ERAS) Program","volume":"15","author":"Forbes C. 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