Machine and Deep Learning Techniques in Cancer Prediction and Risk Stratification Using Bioinformatics in Big Data Era: A Review

Abstract

Cancer remains a global health challenge, and early edge detection is crucial for improving patient outcomes and survival rates. Traditional diagnostic methods often face limitations in sensitivity and specificity, emphasizing the need to innovate approaches to enhance cancer diagnosis. This paper summarizes the recent applications and methodologies of Machine learning(ML) and/or Deep learning(DL) in bioinformatic for cancer prediction and diagnosis and how can be successfully employed to tackle problems such as patient classification, gene clustering, and biomarkers identification. This review constraints on three types of cancer: prostate, gastric, and colorectal.