Prediction of sentinel lymph node metastasis in breast cancer patients based on preoperative features: a deep machine learning approach.

ABSTRACT: Sentinel lymph node (SLN) biopsy is the standard surgical approach to detect lymph node metastasis in breast cancer. Machine learning is a novel tool that provides better accuracy for predicting positive SLN involvement in breast cancer patients. This study obtained data from 2890 surgical cases of breast cancer patients from two referral hospitals in Iran from 2000 to 2021. Patients whose SLN involvement status was identified were included in our study. The dataset consisted of preoperative features, including patient features, gestational factors, laboratory data, and tumoral features. In this study, TabNet, an end-to-end deep learning model, was proposed to predict SLN involvement in breast cancer patients. We compared the accuracy of our model with results from logistic regression anal

SUBMITTER: Shahriarirad R 

PROVIDER: S-EPMC10791698 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature