Utilizing AI to Investigate mental and psychological diseases using EEG

وصف المشروع

Our project aims to improve the diagnosis and treatment of psychiatric conditions. By integrating EEG data with advanced artificial intelligence techniques, this project seeks to provide a more accurate, objective, and efficient approach to diagnosing mental health disorders. The project primarily focuses on analyzing EEG signals, which measure the brain’s electrical activity, to detect patterns associated with various mental health disorders such as Alzheimer’s disease, Major Depressive Disorder (MDD), and Bipolar Disorder. Using advanced machine learning algorithms, including Hybrid CNN-RNN models and transfer learning, the project will enhance diagnostic precision, moving from traditional subjective assessments to data-driven solutions. The goal is to create a model capable of identifying specific neural activity patterns indicative of mental health disorders, ultimately enabling early detection and more personalized treatment plans. This project not only advances scientific understanding of mental health through objective biomarkers but also contributes to the growing field of AI applications in healthcare. By demonstrating the potential of EEG and AI integration, it opens the door for more efficient mental health screenings, ensuring timely interventions that can significantly improve patient outcomes.

مجالات المشروع