AI in neurodegenerative disorders: A neurosurgical perspective

This paper investigates the application of artificial intelligence (AI) in diagnosing and managing neurodegenerative disorders that require neurosurgical intervention, such as Parkinson's disease (PD) and Alzheimer's disease (AD). A systematic review of the literature was conducted to identify studies that utilized AI techniques for diagnosis, treatment planning, or post-operative monitoring of these conditions. The results demonstrate the potential of AI to improve early detection, treatment outcomes, and patient care. However, challenges such as data quality, explainability, and ethical considerations must be addressed to ensure the responsible and effective integration of AI into clinical practice.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2024-10-19
DOI
https://doi.org/10.30574/wjarr.2024.24.1.3173
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.12
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article

AI in neurodegenerative disorders: A neurosurgical perspective

Waseem Asrar Khan, Muhammad Shafiq, S. A. Shafiq, Ahmad Reshad Payenda et al.
1 citations
World Journal of Advanced Research and Reviews
Artificial Intelligence in Healthcare and Education
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article

AI in neurodegenerative disorders: A neurosurgical perspective

Waseem Asrar Khan, Muhammad Shafiq, S. A. Shafiq, Ahmad Reshad Payenda, Yousuf Shafiq, Behesta Shafiq
article en
1 citations

Abstract

This paper investigates the application of artificial intelligence (AI) in diagnosing and managing neurodegenerative disorders that require neurosurgical intervention, such as Parkinson's disease (PD) and Alzheimer's disease (AD). A systematic review of the literature was conducted to identify studies that utilized AI techniques for diagnosis, treatment planning, or post-operative monitoring of these conditions. The results demonstrate the potential of AI to improve early detection, treatment outcomes, and patient care. However, challenges such as data quality, explainability, and ethical considerations must be addressed to ensure the responsible and effective integration of AI into clinical practice.

World Journal of Advanced Research and ReviewsVol. 24(1)
Openalex Percentile: Top 47%
Artificial Intelligence in Healthcare and Education
0.12
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