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This review examines the role of Artificial Intelligence (AI) and Machine Learning (ML) in predicting and managing psychiatric disorders in patients with neurological conditions like epilepsy, Parkinson’s disease, and multiple sclerosis. These disorders often coexist with psychiatric conditions such as dementia, anxiety, and depression, complicating diagnosis and treatment. AI-driven systems, using techniques like predictive analytics, Natural Language Processing (NLP), and adaptive learning, analyze real-time patient data, neurological markers, cognitive assessments, and behavioral patterns. The aim is to enhance diagnostic accuracy, enable early psychiatric disorder detection, and provide personalized treatment plans, ultimately improving patient outcomes and streamlining clinical workflows.

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AI Driven Support System for Neurologists to Integrating Neurological Psychiatric Data

  • 会议论文

  • 发表日期：

    2026年

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  • H. K. Buddhima Kaushalya,
  • N. G. W. Gamage,
  • D. K. O. P. Kumarathunga,
  • K. A. Dilini T. Kulawansa,
  • S. C. Premaratne

摘要

This review examines the role of Artificial Intelligence (AI) and Machine Learning (ML) in predicting and managing psychiatric disorders in patients with neurological conditions like epilepsy, Parkinson’s disease, and multiple sclerosis. These disorders often coexist with psychiatric conditions such as dementia, anxiety, and depression, complicating diagnosis and treatment. AI-driven systems, using techniques like predictive analytics, Natural Language Processing (NLP), and adaptive learning, analyze real-time patient data, neurological markers, cognitive assessments, and behavioral patterns. The aim is to enhance diagnostic accuracy, enable early psychiatric disorder detection, and provide personalized treatment plans, ultimately improving patient outcomes and streamlining clinical workflows.