{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["81"],"submitter":["Jiang F"],"pubmed_abstract":["<h4>Background</h4>Accurate prediction of early recurrence is essential for disease management of patients with non-muscle-invasive bladder cancer (NMIBC). We aimed to develop and validate a deep learning-based early recurrence predictive model (ERPM) and a treatment response predictive model (TRPM) on whole slide images to assist clinical decision making.<h4>Methods</h4>In this retrospective, multicentre study, we included consecutive patients with pathology-confirmed NMIBC who underwent transurethral resection of bladder tumour from five centres. Patients from one hospital (Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China) were assigned to training and internal validation cohorts, and patients from four other hospitals (the Third Affiliated Hospital of Sun Yat-se"],"journal":["EClinicalMedicine"],"pagination":["103125"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11909458"],"repository":["biostudies-literature"],"pubmed_title":["Deep learning-based model for prediction of early recurrence and therapy response on whole slide images in non-muscle-invasive bladder cancer: a retrospective, multicentre study."],"pmcid":["PMC11909458"],"pubmed_authors":["Yang H","Xie Y","Jiang F","Lin T","Hong G","Lin Z","Wang H","Liu Y","Zhu M","Huang S","Xu A","Wu S","Zeng H","Luo Y","Shen R","Wang Y","Chen R"],"additional_accession":[]},"is_claimable":false,"name":"Deep learning-based model for prediction of early recurrence and therapy response on whole slide images in non-muscle-invasive bladder cancer: a retrospective, multicentre study.","description":"<h4>Background</h4>Accurate prediction of early recurrence is essential for disease management of patients with non-muscle-invasive bladder cancer (NMIBC). We aimed to develop and validate a deep learning-based early recurrence predictive model (ERPM) and a treatment response predictive model (TRPM) on whole slide images to assist clinical decision making.<h4>Methods</h4>In this retrospective, multicentre study, we included consecutive patients with pathology-confirmed NMIBC who underwent transurethral resection of bladder tumour from five centres. Patients from one hospital (Sun Yat-sen Memorial Hospital of Sun Yat-sen University, Guangzhou, China) were assigned to training and internal validation cohorts, and patients from four other hospitals (the Third Affiliated Hospital of Sun Yat-se","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Mar","modification":"2025-04-20T00:11:37.981Z","creation":"2025-04-20T00:11:37.981Z"},"accession":"S-EPMC11909458","cross_references":{"pubmed":["40093987"],"doi":["10.1016/j.eclinm.2025.103125"]}}