AI-Driven Early Detection of Chronic Diseases: A Paradigm Shift in Preventive Healthcare
Abstract
Chronic diseases like diabetes, hypertension, and cardiovascular disorders impose a significant burden on global healthcare systems. This paper explores the use of AI algorithms in early detection and risk assessment of chronic diseases. Techniques such as deep learning, predictive analytics, and ensemble models are evaluated for their accuracy and scalability. Case studies highlight successful implementations in real-world healthcare settings. The paper discusses challenges like data privacy, algorithmic bias, and integration into clinical workflows, proposing strategies for effective adoption.
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