Paper Contents
Abstract
Our application revolutionizes depression detection by analyzing facial expressions without intrusive devices. Using advanced technology and the Resnetv52 Convolutional Neural Network (CNN) model, we extract key features like eyebrow movements, lip patterns, and nasal expressions to identify signs of depression. Users can access our platform for screening tests directly from their devices. If depressive symptoms are detected, our platform connects them with certified medical professionals for diagnosis and ongoing evaluation. Our system generates detailed reports on depression severity and treatment options. Designed for user privacy and confidentiality, patient data is securely stored and accessible only to authorized medical personnel. The platform ensures seamless communication between patients and doctors, supporting ongoing consultation and treatment. Patients can track their progress and access their medical history anytime, aiding informed decision-making and continuity of care. Our innovative approach aims to improve mental health outcomes and enhance overall well-being.
Copyright
Copyright © 2024 ALAN JOSEPH. This is an open access article distributed under the Creative Commons Attribution License.
