Abstract:BackgroundBladder cancer, one of the most prevalent cancers globally, can be regarded as considerable morbidity and mortality for patients. The bladder is an organ that comes in constant exposure to the environment and other risk factors such as inflammation.AimsIn the current study, we used machine learning (ML) methods and developed risk prediction models for bladder cancer.MethodsThis population‐based case–control study is focused on 692 cases of bladder cancer and 692 healthy people. The ML, including Neur… Show more
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