Health data science is a rapidly evolving field that integrates biostatistics, programming, and artificial intelligence/machine learning (AI/ML) to tackle pressing challenges in public health, biomedical sciences, clinical care, and biobehavioral sectors. This session aims to demystify the hype surrounding health data science and demonstrate how health agencies and professionals can transform data into actionable insights to enhance healthcare outcomes. We will explore how AI and predictive analytics are leveraged to improve patient care and health management, such as in analyzing patient data to predict the risk of chronic disease or to identify health disparities and assess community health needs. Panelists will explore the need to continuously evaluate the impact of data science initiatives and refine approaches based on feedback and outcomes. We will discuss actions agencies are taking to improve access to data and the quality and integrity of health data, and how outcomes are measured. We will also explore how agencies can work to ensure ethical and bias-free data and model usage and outcomes.

Join us for an insightful session that goes beyond the hype and delves into the practical applications of health data science. Learn how to harness the power of AI and predictive analytics to drive meaningful improvements in healthcare quality and patient outcomes.