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Data from 27 PwMS, monitored over two months were analyzed with several state-of-the-art ML models to predict the efficacy of a computerized cognitive intervention targeting cognitive decline. A model based on Support Vector Machines achieved high accuracy in identifying patient response within the first 2-3 weeks of intervention, aided by feature selection methods like Mutual Information and Recursive Feature Elimination. 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