Survival Analysis of Cancer Patients Using Machine Learning Technique by Shakuntala Baichoo
Explore survival analysis techniques for cancer patients using machine learning in this comprehensive lecture. Delve into the application of advanced computational methods to predict and analyze patient outcomes based on clinical and lifestyle parameters. Learn how to harness modern mathematical approaches to better understand health-related data, with a focus on cancer research. Discover the potential of various machine learning techniques, including logistic regression, tree-based methods, support vector machines, Bayesian methods, and deep networks, in the context of biomedicine and health. Gain insights into predicting individual patient outcomes, analyzing medical imaging data, genomic variant analysis, and identifying patterns in large-scale heterogeneous datasets. Bridge the gap between mathematical modeling and clinical problems while exploring the possibilities of building public health databases as valuable resources for future research and analysis.