Predict survival for cancer patients using real world data: simple model or advanced machine learning?

Abstract

Predicting the survival for cancer patients is important for informative medical decision making. When machine learning is applied more and more into different areas, it is appealing to evaluate at what extent we can predict survival for cancer patients from electronic health record data. This presentation will use one real example to discuss the advantage of the real world data and challenge of the problem. We will also show the performance of different models/approaches, from simple model to advanced machine learning.