DEVELOPMENT OF INTELLIGENT ALGORITHMS FOR MEDICAL IMAGE ANALYSIS IN THE DIAGNOSIS OF NEURODEGENERATIVE DISEASES

Neurodegenerative diseases represent a major challenge in modern healthcare due to their progressive nature and difficulty in early diagnosis. This study investigates the application of artificial intelligence techniques for analyzing medical imaging data to detect neurodegenerative disorders. In particular, deep learning algorithms such as Convolutional Neural Network are applied to analyze Magnetic Resonance Imaging (MRI) data for identifying structural changes in the brain. The proposed approach integrates medical image preprocessing, feature extraction, and machine learning classification. Experimental results demonstrate that AI-based diagnostic models significantly improve accuracy in detecting diseases such as Alzheimer’s disease and Parkinson’s disease. The proposed method can assist clinicians in early diagnosis and improve decision-making in neurological healthcare.