We aim to predict individualized/personalized recovery trajectories based on algorithms from brain markers, big data, and computational modeling. In this regard, I will cover three topics:
- Using machine learning to predict recovery after stroke where we examine neuroimaging scans to extract features that best predict stroke recovery,
- Using AI to simulate individual patient recovery trajectories after treatment, we have developed algorithms to predict recovery as a function of rehabilitation. In this project, we also examine predictors of treatment outcomes in bilingual aphasia
- using big data mining to create a therapy calculator for aphasia recovery. In the last project, we are building algorithms for therapy outcomes based on a large amount of rehabilitation data using a digital therapeutic Constant Therapy. This recent work has the potential to provide personalized recommendations for rehabilitation trajectories for individual patients who have suffered from acquired brain injury.
