A Comprehensive Risk Assessment of Genetical Disorders in Children

Abstract

The Genetical Disorder Risk Assessment System presents a web-based application of genetic disorder risk assessment through AI-powered face analysis and dynamic questionnaires. The system seeks to offer early, accessible, and personalized information regarding possible genetic health risks. Registration and face detection- based identification are performed using a webcam. The facial features detected are analyzed to estimate the age group of the user. Depending on the age detected, a suitable questionnaire is dynamically selected. The questionnaire gathers important information regarding family history, lifestyle, and general health indicators. An educated machine learning model processes the user's answer to estimate the risk of genetic disorders. The model provides a percentage risk value and labels the outcome as high, medium, or low. The system doesn't depend on uploaded medical records, increasing convenience and ease of use. Age based detection on faces guarantees that questionnaires are age relevant and tailored. The user-friendly web interface supports health awareness among non-expert users. Instant feedback enables users to take early preventive health measures. The project focuses on privacy ensuring safe processing and storage of user information. By integrating facial recognition, dynamic form creation, and AI based analysis the system offers an innovative method of early diagnosis. The tool has the ability to assist individuals and healthcare professionals in proactive genetic health.