Comparison of machine learning models for predicting the risk of breast cancer-related lymphedema in Chinese women

ABSTRACT:

Objective

Predictive models for the occurrence of cancer symptoms by using machine learning (ML) algorithms could be used to aid clinical decision-making in order to enhance the quality of cancer care. This study aimed to develop and validate a selection of classification models that used ML algorithms to predict the occurrence of breast cancer-related lymphedema (BCRL) among Chinese women.

Methods

This was a retrospective cohort study of consecutive cases that had been diagnosed with breast cancer, stages I-IV. Forty-eight variables were grouped into five feature sets. Five classification models with ML algorithms were developed, and the models' performance and the variables’ relative importance were assessed accordingly.

Results

Of 370 eligible female participa

SUBMITTER: Wu X 

PROVIDER: S-EPMC9579303 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature