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Diagnosing Schizophrenia from Brain Activity

Computational Psychiatry is growing trend that applies machine learning methods to psychological disorders. How well can we predict schizophrenia diagnosis from brain activity? This project uses neuroimaging tools from Nilearn, and machine learning tools from scikit-learn to differentiate patients diagnosed with schizophrenia from healthy controls using resting state fmri data.

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This is an example project page which serves as a template

Each project repository should have a markdown file explaining the background and objectives of the project, as well as a summary of the results, and links to the different deliverables of the project. Project reports are incorporated in the BHS website.

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