Aggregated Pattern Classification Method for improving neural disorder stage detection.

Journal: Brain and behavior
PMID: 39169422

Abstract

BACKGROUND: Neurological disorders pose a significant health challenge, and their early detection is critical for effective treatment planning and prognosis. Traditional classification of neural disorders based on causes, symptoms, developmental stage, severity, and nervous system effects has limitations. Leveraging artificial intelligence (AI) and machine learning (ML) for pattern recognition provides a potent solution to address these challenges. Therefore, this study focuses on proposing an innovative approach-the Aggregated Pattern Classification Method (APCM)-for precise identification of neural disorder stages.

Authors

  • Mohd Anjum
    Department of Computer Engineering, Aligarh Muslim University, Aligarh, India.
  • Sana Shahab
    Department of Business Administration, College of Business Administration, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
  • Shabir Ahmad
    Department of Computer Engineering, College of IT Convergence, Gachon University, Seongnam, Republic of Korea.
  • Sami Dhahbi
    Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Abha, Saudi Arabia.
  • Taegkeun Whangbo
    Department of Computer Engineering, College of IT Convergence, Gachon University, Seongnam, Republic of Korea.

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