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This paper provides a comprehensive review of the application of Artificial Intelligence (AI) based learning methods in the early identification and monitoring of cognitive decline characterizing many neurological disorders. Traditional methods for assessment and diagnosis of cognitive decline have proved ineffective. AI-based approaches have demonstrated potential in improving accuracy, efficiency, and early detection. This manuscript empirically investigates the various AI techniques, their applications, challenges, and how effective intelligent solutions can be developed.

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An Empirical Analysis of AI Based Learning Methods in Identification of Cognitive Decline in Neurodegenerative Disorders

  • 会议论文

  • 发表日期：

    2025年

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  • Ritika Wason,
  • Parul Arora,
  • M. N. Hoda,
  • Devansh Arora

摘要

This paper provides a comprehensive review of the application of Artificial Intelligence (AI) based learning methods in the early identification and monitoring of cognitive decline characterizing many neurological disorders. Traditional methods for assessment and diagnosis of cognitive decline have proved ineffective. AI-based approaches have demonstrated potential in improving accuracy, efficiency, and early detection. This manuscript empirically investigates the various AI techniques, their applications, challenges, and how effective intelligent solutions can be developed.