Survey on Machine Learning-Based Prognosis of Early-Stage Alzheimer's Disease

Authors

  • Sofiyana Inamdarr  Nutan Maharashtra Institute of Engineering and Technology, Pune, Maharashtra, India
  • Pritee Joshi  Nutan Maharashtra Institute of Engineering and Technology, Pune, Maharashtra, India
  • Amreen Parveen Khan  Nutan Maharashtra Institute of Engineering and Technology, Pune, Maharashtra, India
  • Chetan Patil  Nutan Maharashtra Institute of Engineering and Technology, Pune, Maharashtra, India
  • Nitin Wankhade  Nutan Maharashtra Institute of Engineering and Technology, Pune, Maharashtra, India
  • Chandrakant Kokane  

Keywords:

Alzheimer's, Machine Learning, AI, Image, MRI

Abstract

Alzheimer's disease (AD) is a progressively worsening neurological condition that poses an increasing concern to global public health. Timely identification and precise diagnosis of Alzheimer's disease are essential for effective intervention and care. This comprehensive review delves into an extensive examination of methods for detecting Alzheimer's disease (AD), with a specific emphasis on approaches centered around medical imaging. We explore the spectrum of imaging modalities, data acquisition, feature extraction, classification techniques, and the latest advancements in AI-based diagnostic systems. Through a comprehensive review of the literature, we highlight the evolving landscape of AD detection, challenges, and future research directions. This survey aims to serve as a valuable resource for researchers, clinicians, and policymakers in the field of AD detection.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-11-30

Issue

Volume 9, Issue 6, November-December-2023

Section

Research Articles

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How to Cite

[1]
Sofiyana Inamdarr, Pritee Joshi, Amreen Parveen Khan, Chetan Patil, Nitin Wankhade, Chandrakant Kokane, " Survey on Machine Learning-Based Prognosis of Early-Stage Alzheimer's Disease" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 6, pp.126-138, November-December-2023.