Authors: Y Kushi Reddy, Yallamanchi Himabindu, Anish NC, CV Anusha Reddy, S Harshit Sai,
Abstract: In recent years, the integration of artificial intelligence (AI) into healthcare has enabled innovative approaches for early disease detection and diagnosis. This paper presents the design and development of an AI-powered mobile application that performs preliminary health diagnosis based on user-reported symptoms. The proposed system utilizes machine learning models trained on verified medical datasets to identify possible health conditions from input symptoms, aiming to assist users in seeking timely medical consultation. The application is built using Python, TensorFlow, and a Flask-based backend, with a simple and interactive user interface. The system also emphasizes user privacy and data security. Testing demonstrates the model’s potential to deliver reliable symptom-based predictions, thereby offering a scalable and accessible solution to basic health assessment. This project showcases how AI technologies can be effectively applied in the medical domain to bridge gaps in early diagnosis and promote preventive healthcare.
DOI: http://doi.org/
