The aims of this study were: (1) to test the feasibility of using a deep learning model with 7T sMRI as an input to predict cognition levels (CLs) at the single-subject level, and (2) to investigate whether the inclusion of CLs estimation could facilitate the classification for early psychosis (EP) patients and healthy controls (HCs). Promising accuracy was achieved in estimating CLs and the inclusion provides considerable classification improvement. Fivefold cross-validating experiments demonstrated higher classification AUC-ROC scores over published methods. Therefore, deep learning can be used to estimate CLs and CL estimation improves the classification performance of EP.
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