Combining Machine Learning and Modeling Approaches to Forecasting Disease Progression

Explore a 36-minute lecture on integrating machine learning and modeling techniques for predicting disease progression, delivered by Mohammad Kohandel from the University of Waterloo. Gain insights into cutting-edge approaches in mathematical oncology as part of the Fields Institute's Thematic Program on Mathematical Oncology and the Ecology and Evolution of Cancer series. Delve into the innovative methods used to forecast disease trajectories, combining the power of machine learning with traditional modeling approaches. Understand how these interdisciplinary techniques are advancing our ability to predict and potentially intervene in disease progression, particularly in the context of cancer research.

Combining machine learning and modeling approaches to forecasting disease progression