Rajat Thomas

“Predicting treatment outcomes for psychiatric disorders”

“Can we use non-invasive methods like functional magnetic resonance imaging (fMRI) to predict the effectiveness of a treatment in neuropsychiatric
disorders? Would it be possible to design a treatment strategy personalized to the patient?
The answers to these questions might lie in the complex spatio-temporal patterns of the so called resting-state brain activity, i.e., the spontaneous response
of the brain when it is not engaged in some explicit task.
Current state-out-the-art machine learning techniques like Deep Learning provide us with the tools to uncover such distinguishing patterns in the resting
state to reliably predict the response of patients to treatment. This project entails therefore the design, testing and deployment of such machine learning algorithms.”

Project start: March 2016
Position: Post doc
Email: (Enable Javascript to see the email address)