An Assessment of the Predictive Performance of Current Machine Learning-Based Breast Cancer Risk Prediction Models: Systematic Review.

ABSTRACT:

Background

Several studies have explored the predictive performance of machine learning-based breast cancer risk prediction models and have shown controversial conclusions. Thus, the performance of the current machine learning-based breast cancer risk prediction models and their benefits and weakness need to be evaluated for the future development of feasible and efficient risk prediction models.

Objective

The aim of this review was to assess the performance and the clinical feasibility of the currently available machine learning-based breast cancer risk prediction models.

Methods

We searched for papers published until June 9, 2021, on machine learning-based breast cancer risk prediction models in PubMed, Embase, and Web of Science. Studies describing the development

SUBMITTER: Gao Y 

PROVIDER: S-EPMC9837707 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature