Al Scott Prize Lecture
Fri, 04/20/2018 - 3:00pm
Traditionally, medicine has taken a discrete viewpoint of disease, whereby patients are diagnosed into bins where corresponding treatments have been assigned. While this is effective for many simple conditions, more complex diseases such as cancer have proved difficult to treat under this paradigm. With model-based precision medicine, we collect as much patient-specific information as possible, then employ mathematical and computational models to select and optimize patient-specific treatments. One of the most useful forms of patient-specific data is imaging, but image data is always noisy and incomplete, and this contributes to uncertainty in predicted treatment outcomes. In this talk, we will discuss how to analyze imaging systems in the context of model-based precision medicine.