Machine Learning Applications for Early Detection and Intervention in Chronic Diseases
Abstract
This research paper explores the application of machine learning (ML) in early detection and intervention strategies for chronic diseases. Recognizing the significant impact of chronic conditions on global health, the study investigates how ML algorithms can leverage diverse datasets to identify patterns, predict risks, and facilitate timely interventions. The research delves into case studies and implementations across various chronic diseases, emphasizing the potential for personalized healthcare solutions. Ethical considerations, challenges, and the future prospects of ML in this domain are also discussed. The findings contribute to advancing the understanding of ML's role in proactive healthcare management for chronic diseases.
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