Neuro-AI Synergy in Visual and Motor Healthcare: Redefining Diagnosis Through Brain, Eye, and Motion Data

Authors

  • Abdullah Mazharuddin Khaja Masters of science, Computer Science Governors State university
  • Hira Rafi Postdoctoral Fellow Department of Neuroscience Northwestern University
  • Michidmaa Arikhad Department of computer science American National University, Louisville Kentucky

DOI:

https://doi.org/10.5281/zenodo.16470659

Keywords:

Artificial Intelligence, Neuroscience, EEG

Abstract

This paper delves into the transformative potential of Artificial Intelligence (AI) in neuro-visual healthcare by emphasizing the intricate synergy between brain function, visual perception, and motor behavior. It presents a forward-looking framework designed to elevate diagnostic precision and therapeutic efficiency through the intelligent fusion of multimodal data. By harnessing advanced AI techniques to analyze and correlate neurological signals (EEG), eye-tracking patterns, and motion dynamics.[1]. we propose a robust diagnostic architecture capable of delivering real-time, data-driven clinical insights. This integrated approach not only supports early detection of complex neurological and neurodegenerative conditions but also paves the way for highly personalized and adaptive healthcare solutions tailored to individual patient profiles[2].

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Published

2025-06-29

How to Cite

Khaja, A. M., Rafi, H., & Arikhad, M. (2025). Neuro-AI Synergy in Visual and Motor Healthcare: Redefining Diagnosis Through Brain, Eye, and Motion Data. International Journal of Science and Engineering Science Research, 1(2), 54–60. https://doi.org/10.5281/zenodo.16470659

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Articles
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