Predictive Analytics for Disease Management

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Overview

This lecture is part of the 3rd Public Health Conference in 2025, offering healthcare professionals the opportunity to explore innovative AI solutions for managing chronic diseases, ultimately improving health outcomes and system efficiency. This year's theme emphasizes the role of artificial intelligence (AI) in addressing the challenges posed by chronic diseases, which significantly burden healthcare systems globally.

What I will learn?

  • •Discuss the role of artificial intelligence in enhancing predictive modeling for patient outcomes.
    •Identify key applications of AI and predictive analytics in managing chronic diseases, infectious diseases, and mental health conditions.
    •Examine various data sources used in predictive analytics, including electronic health records (EHRs), genomic data, and social determinants of health.
    •Discuss the importance of data integration and preprocessing for effective predictive modeling.
    •Evaluate how predictive analytics can improve patient outcomes through early intervention, personalized treatment plans, and proactive care management.
    •Discuss the implications of predictive insights for healthcare providers and patients.

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