Dementia is a growing concern worldwide, with its prevalence expected to rise as the global population ages. Early detection of dementia and cognitive impairments is crucial for providing timely intervention and improving quality of life. This project aims to develop an AI-based web application for dementia risk screening, leveraging synthetic data for model training. The system offers a comprehensive risk assessment using cognitive and attention tests such as the Word Recall Memory Assessment, Number Sequencing Attention Test, and Speech-Based Verbal Fluency Test. The platform is designed for both administrators and users, providing functionalities like user management, test attempts, automated risk evaluation, and detailed reports. Admin users can manage users and access risk analysis reports, while regular users can attempt the cognitive tests and view their risk reports. The system employs machine learning algorithms to predict the likelihood of cognitive impairment, categorizing users into three risk levels: No Cognitive Risk, Mild Cognitive Risk, and High Dementia Risk. This web-based tool is designed to be user-friendly, providing an intuitive interface for individuals to evaluate their cognitive health and aiding healthcare professionals in early detection. The final output of the project includes automated risk analysis and downloadable reports, contributing to efficient dementia diagnosis and monitoring.

Keywords: Dementia, Cognitive Risk, AI, Web Application, Machine Learning, Cognitive Tests, Risk Assessment, Early Detection.