Cutting-Edge Machine Learning and Mathematical Approaches in Cancer Prognosis and Therapy: Progress and Challenges

Abstract

The disease entity known as coronary artery disease continues to be the major cause of heart attacks and deaths among people globally. Early identification of CAD necessitates prompt action for effective intervention. This study looks at the ways that machine learning (ML) and artificial intelligence (AI) techniques aid in the early detection and diagnosis of coronary artery disease.

Methods: The study assessed a thorough analysis of published research that employed machine learning and artificial intelligence techniques to identify colon cancer. When examining research articles, the researchers used the databases PubMed, IEEE Xplore, and Scopus.

Results: AI-based models that combine deep learning and machine learning algorithms provide effective analysis of imaging data, clinical characteristics, and biomarkers for the early detection of CAD. The newly created diagnostic techniques have shorter examination times and more diagnostic accuracy than conventional techniques.

Conclusion: Using AI and ML diagnostic techniques that are beyond human detection skills, scores of inconspicuous patterns contained in large databases can be found. Current applied AI and ML systems in medical infrastructure encounter resistance due to programming issues with discriminator algorithms and inaccurate data, as well as adoption issues in healthcare institutions. The accuracy models should be developed further and methodically incorporated into clinical procedures.