Prediction of non-muscle invasive bladder cancer recurrence using machine learning of quantitative nuclear features
Abstract
Non-muscle invasive bladder cancer (NMIBC) generally has a good prognosis; however, recurrence after transurethral resection (TUR), the standard primary treatment, is a major problem. Clinical management after TUR has been based on risk classification using clinicopathological factors, but these classifications are not complete. In this study, we attempted to predict early recurrence of NMIBC based on machine learning of quantitative...
Paper Details
Title
Prediction of non-muscle invasive bladder cancer recurrence using machine learning of quantitative nuclear features
Published Date
Apr 1, 2022
Journal
Volume
35
Issue
4
Pages
533 - 538
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