Lifestyle and occupational risks assessment of bladder cancer using machine learning-based prediction models.

ABSTRACT:

Background

Bladder 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.

Aims

In the current study, we used machine learning (ML) methods and developed risk prediction models for bladder cancer.

Methods

This population-based case-control study is focused on 692 cases of bladder cancer and 692 healthy people. The ML, including Neural Network (NN), Random Forest (RF), Decision Tree (DT), Naive Bayes (NB), Gradient Boosting (GB), and Logistic Regression (LR), were applied, and the model performance was evaluated.

Results

The RF (AUC = .86, precision = 79%) had the best performanc

SUBMITTER: Shakhssalim N 

PROVIDER: S-EPMC10480417 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature