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MACHINE LEARNING METHODS FOR PREDICTING POST-STROKE APHASIA AND LANGUAGE RECOVERY - PROJECT SUMMARY/ABSTRACT APHASIA IS ONE OF THE MOST DEVASTATING CONSEQUENCES OF STROKE, YET CLINICIANS ARE UNABLE TO PROVIDE A PERSONAL-

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MACHINE LEARNING METHODS FOR PREDICTING POST-STROKE APHASIA AND LANGUAGE RECOVERY - PROJECT SUMMARY/ABSTRACT APHASIA IS ONE OF THE MOST DEVASTATING CONSEQUENCES OF STROKE, YET CLINICIANS ARE UNABLE TO PROVIDE A PERSONAL- IZED PROGNOSIS TO PEOPLE WITH APHASIA (PWA) DUE TO THE COMPLEX AND MULTIDIMENSIONAL COMBINATION OF FACTORS THAT HAVE THE POTENTIAL TO INFLUENCE RECOVERY. NEUROIMAGING STUDIES OF APHASIA LARGELY FOCUS ON A SINGLE DATA MODALITY AND A RESTRICTED SET OF FEATURES, WHICH CONTRIBUTE ONLY A PIECE OF THE PUZZLE. THUS, THERE IS A CRITICAL NEED FOR A MUL- TIMODAL EXPLORATION OF APHASIA R

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