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AI aids in standardizing assessments like EREFS and EoEHSS, identifies molecular phenotypes and novel biomarkers, and predicts treatment responses, facilitating precision medicine. However, challenges exist: \u201cblack box\u201d issues demand explainable AI (XAI) for trust; validation in large, diverse cohorts, ensuring model generalization, and regulatory approval are crucial; data governance, privacy, and algorithmic integrity require attention. Future priorities include researching pediatric populations, improving treatment response prediction, and developing non-invasive monitoring tools. 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