Autistic spectrum disorders and schizophrenia spectrum disorders are two typical neurodevelopmental disorders. Recent findings suggest that despite the different onset age, these two disorders share quite a lot of common genes, cognitive, emotional and social impairments.
Affective forecasting is the ability to predict future emotions, which is very important for optimal everyday life functioning. Empirical findings suggest that patients with schizophrenia exhibit reduced ability to predict future emotions which may affect their negative symptoms and ultimate functional ability.
Machine learning has been increasingly utilized to optimize the use of brain imaging data in clinical classification and to build predictive models for patients with schizophrenia. Assessing generalizability is one of the most important steps in evaluating predictive models but is surprisingly seldom conducted in clinical studies.
