Predicting Individualized Rehabilitation Outcomes based on Brain and Behavioral Biomarkers

FALL 2019 RESEARCH INCUBATION AWARDEES

PI: Swathi Kiran, Associate Dean, SAR
Co-PI: Margrit Betke, Professor of Computer Sciences, CAS
Track: Digital Health Initiative & Artificial Intelligence Research

Over 2 million people are currently living with aphasia due to a stroke, and the patients do not know whether they will ever recover to improve their communication/cognitive skills. Aphasia therapy is prescribed largely on clinical presentation but the information about brain or behavior that may impact recovery is not taken into account. This project aims to develop machine-learning algorithms that take as input a complex set of brain and behavioral markers to classify and predict responders and non-responders to therapy. This study takes an important first step to predict individualized rehabilitation outcomes. All the data is already collected and the proposed project is ready to be implemented.