The Role of Predictive Analytics in Disease Prevention : A Technical Overview
DOI:
https://doi.org/10.32628/CSEIT24106174Keywords:
Predictive Analytics, Healthcare AI, Disease Prevention, Risk Stratification, Data IntegrationAbstract
This article explores the transformative potential of predictive analytics in healthcare, focusing on its applications in disease prevention and public health management. It examines the power of data integration from diverse sources, the use of predictive modeling for risk stratification, and the broader implications for public health surveillance and chronic disease management. The article also discusses the significant growth of AI in the healthcare market and highlights successful implementations of predictive analytics across various medical domains. Additionally, it addresses the key challenges in implementing these technologies, including data privacy concerns, integration issues, model accuracy, and ethical considerations. Through numerous case studies and statistical evidence, the article demonstrates how predictive analytics is revolutionizing healthcare by enabling more accurate, personalized, and proactive approaches to disease prevention and management.
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