Aggregated Pattern Classification Method for improving neural disorder stage detection

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.