Publications

This paper presents an automated system for interpreting ECG and EEG signals using machine learning to enable early diagnosis of neurological disorders. The model achieves high accuracy, sensitivity, and specificity through advanced feature extraction and classification techniques. Real-time signal processing and noise filtering ensure reliable performance in clinical settings. The proposed solution aims to assist medical professionals in faster and more accurate diagnosis.