Use of Big Data Analytics in Healthcare Research by Rajiv Raman

Explore the application of big data analytics in healthcare research through this informative conference talk. Gain insights into how modern mathematical and computational techniques can be harnessed to better understand health-related data across multiple domains. Learn about various machine learning techniques, including logistic regression, tree-based methods, support vector machines, Bayesian methods, and deep networks, with examples of their applicability in biomedicine and health. Discover how these techniques can be used to predict outcomes for individual patients, analyze medical imaging data, perform genomic variant analysis, and infer patterns in large-scale heterogeneous data. Understand the importance of bridging the gap between mathematical modeling and clinical problems, and explore the potential for building public health databases as valuable resources for research and analysis.