Age-Specific Comparative Analysis of ML Algorithms for Colon Cancer Classification Using Gene Expression Data

ABSTRACT: The field of machine learning (ML) has made significant contributions to the medical domain, notably in the automatic classification of cancer types such as colon cancer. This type of cancer, while generally more common among the elderly, can affect people at any age. The incorporation of ML techniques has minimized the reliance on manual examination and enhanced the capacity to process large datasets in medical research. Utilizing advanced gene technology and analysis of gene expression data, this study addresses the challenges posed by the high dimensionality and limited size of such datasets. The findings reveal that most of the ML models employed here have surpassed expected accuracy levels, highlighting their effectiveness in the precise classification and diagnosis of colon cancer. Consequently, these developments hold promise for improving patient care and the overall efficiency of healthcare services in dealing with colon cancer.