Litcius/Paper detail

Development and International Evaluation of an Artificial Intelligence–based Model (PROGRxN-BCa) Using the World Health Organization 2004/2022 Grading System to Predict Progression Risk and Improve Substratification for Non–muscle-invasive Bladder Cancer

Jethro C.C. Kwong, Zizo Al‐Daqqaq, Yashan Chelliahpillai, Soomin Lee, Kellie Kim, Maximiliano Ringa, Andrew Feifer, Katherine Lajkosz, Marian S. Wettstein, Amy Chan, TaeWeon Lee, Myky Nguyen, Wassim Kassouf, Peter C. Black, Rodney H. Breau, Michele Lodde, Adrian Fairey, Jean‐Baptiste Lattouf, Claudio Jeldres, Ricardo Rendon, Nimira Alimohamed, Neil Fleshner, Romain Diamand, Paolo Gontero, Richard Sylvester, Bas W.G. van Rhijn, Ashish M. Kamat, Alistair E. W. Johnson, Alexandre R. Zlotta, Girish S. Kulkarni

2025European Urology7 citationsDOI

Topics & Concepts

MedicineBladder cancerRisk stratificationGrading (engineering)CohortRisk assessmentMedical physicsIntensive care medicineMEDLINECohort studyHealthcare systemOncologyBladder tumorGeneral surgeryNeoplasm stagingPublic healthPredictive value of testsBladder and Urothelial Cancer TreatmentsFerroptosis and cancer prognosisProstate Cancer Diagnosis and Treatment