Transforming Preventive Healthcare with Machine Learning Technologies

Abstract

In this paper, we explore the transformative role of machine learning (ML) in preventive healthcare (PHC), a proactive approach to health management that aims to prevent diseases and promote overall well-being. We begin by providing an overview of PHC, its importance, and its applications across various healthcare settings. The manuscript then presents a brief review of ML techniques in this field, examining their potential to revolutionize early disease detection, personalized risk assessment, and targeted interventions. We review key studies that demonstrate the capabilities of ML in areas such as cancer screening, cardiovascular risk prediction, population health management, and traditional medicine. By synthesizing current research and identifying future directions, this work aims to enhance the understanding of how ML is reshaping the PHC domain, potentially improving health outcomes and reducing healthcare costs.