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. 

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 improve efficiencies in delivering positive health outcomes. The panel will explore how AI and predictive analytics are utilized to improve patient care and health management, including analyzing patient data to predict the risk of chronic diseases, identifying health disparities, and assessing the impact of nationwide chronic illnesses. Panelists will examine the importance of continually evaluating the impact of data science initiatives and refining approaches based on feedback and outcomes. They will discuss the actions agencies are taking to improve efficient access to data, the quality and integrity of health data, and how outcomes are measured. The session will also explore how agencies can work to ensure the ethical and bias-free use of data and models, as well as their outcomes. 

Potential Topics: 

• Transforming Data into Actionable Insights 

• Improving Data Access and Quality 

• Ethical and Bias-Free Data Usage 

• Health Data Science: Future Directions and Innovations