Data- Access, Analysis and Distillation by K VijayRaghavan

Explore the critical aspects of data management in health and disease research through this insightful lecture by K VijayRaghavan. Delve into the processes of data access, analysis, and distillation as part of the "Machine Learning for Health and Disease" program. Gain valuable insights into how modern mathematical and computational techniques can be applied to better understand health-related data across multiple domains. Learn about the challenges and opportunities in bridging the gap between mathematical modeling and clinical problems, and discover the potential of machine learning in predicting patient outcomes, analyzing medical imaging, and inferring patterns in large-scale heterogeneous data. This lecture is ideal for PhD students in STEM fields, medical students, postdoctoral fellows, faculty, and professionals in science, engineering, and medicine seeking to enhance their understanding of data-driven approaches in healthcare.