Linear regression algorithm for cancer detection

Abstract

Cancer is recognized as a diverse ailment encompassing numerous subtypes. Early identification and prognosis of cancer types are crucial in the realm of cancer research, aiding subsequent clinical interventions. The necessity to categorize cancer patients into high or low-risk groups has spurred extensive exploration within the biomedical and bioinformatics domains into the potential applications of machine learning (ML) methodologies. Consequently, these approaches have been harnessed to model cancer progression and treatment, with the added advantage of extracting key features from intricate datasets.