Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer patients

Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer patients

Abstract Muscle-Invasive Bladder Cancer (MIBC) is a more aggressive disease than non-muscle-invasive bladder cancer (NMIBC), with greater chances of metastasis. We sought to develop machine learning (ML) models to predict metastasis and prognosis in MIBC patients. Clinical data of MIBC cases from 20...

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Bibliographic Details
Main Authors: Qian Deng, Shan Li, Yuxiang Zhang, Yuanyuan Jia, Yanhui Yang
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Machine learning
Muscle-Invasive bladder Cancer
Distant metastasis
Prognosis prediction
SEER
Online Access:https://doi.org/10.1038/s41598-025-96089-1
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https://doi.org/10.1038/s41598-025-96089-1

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