Transforming Preventive Healthcare with Machine Learning Technologies

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.

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Publication Details

Journal
Journal of Operations Intelligence
Published
2025-04-07
DOI
https://doi.org/10.31181/jopi31202538
Citations
3
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
8.81
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article

Transforming Preventive Healthcare with Machine Learning Technologies

Zahra Zare, Mümtaz Karataş, Yu‐Jun Zheng
3 citations
Journal of Operations Intelligence
Artificial Intelligence in Healthcare
8.81
article

Transforming Preventive Healthcare with Machine Learning Technologies

Zahra Zare, Mümtaz Karataş, Yu‐Jun Zheng
article en
3 citations

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.

Journal of Operations IntelligenceVol. 3(1)
Wright State University (US), Affiliated Hospital of Hangzhou Normal University (CN)
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare
8.81
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Transforming Preventive Healthcare with Machine Learning Technologies — Zahra Zare, Mümtaz Karataş, et al. · Journal of Operations Intelligence (2025) | TGRS Research Map | TGRS