Application of Machine Learning Algorithm for Breast Cancer Detection: A Thematic Analysis

Abstract

This study aims to review different machine learning models with acceptable generalization capacity and clinical explainability based on two features; first to measure the association between independent variables (breast cancer risk and preventive factor) and dependent variable (existence of cancer). Secondly to explore the patterns and correlations in raw data, over time and case, and continuously learn and improve. For the collection of data, academic databases; ScienceDirect and PubMed were used to find the articles. These articles were then analyzed through NVivo for content analysis. The study conjectured that machine learning and artificial intelligence are helping the oncologist in the early detection of breast cancer which resultantly increases the survival rate of the patients. The above findings aim to stimulate the process of cancer scanning at an early stage and also point out the new horizon of health application to the AI experts.