Predicting Breast Cancer in Chinese Women Using Machine Learning Techniques: Algorithm Development.

ABSTRACT:

Background

Risk-based breast cancer screening is a cost-effective intervention for controlling breast cancer in China, but the successful implementation of such intervention requires an accurate breast cancer prediction model for Chinese women.

Objective

This study aimed to evaluate and compare the performance of four machine learning algorithms on predicting breast cancer among Chinese women using 10 breast cancer risk factors.

Methods

A dataset consisting of 7127 breast cancer cases and 7127 matched healthy controls was used for model training and testing. We used repeated 5-fold cross-validation and calculated AUC, sensitivity, specificity, and accuracy as the measures of the model performance.

Results

The three novel machine-learning algorithms (XGBoost, Ra

SUBMITTER: Hou C 

PROVIDER: S-EPMC7308891 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature