Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{202305,
        author = {Samridhi Tyagi and Taniya and Tanvi Gupta and Khushi Gupta and Anil Kumar Yadav},
        title = {MultiDiag-X: AI-Powered Multi-Disease Risk Prediction and Medical Report Analyzer},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {6649-6655},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202305},
        abstract = {Understanding medical reports can be difficult for individuals without a medical background. MultiDiag-X is an AI-based system developed to simplify medical report interpretation and provide early risk awareness for diseases such as heart disease and diabetes. The system analyzes basic health data and medical reports to identify abnormal values and present them in simple, easy-to-understand language. It also uses explainable AI techniques to show the factors influencing predictions, improving transparency and trust. Based on the predicted risk levels, the system offers responsible guidance, helping users decide whether to maintain their lifestyle, monitor their health, or consult a doctor. This project focuses on improving health awareness and supporting informed decisions without replacing professional medical advice.},
        keywords = {Artificial Intelligence, Machine Learning, Disease Risk Prediction, Heart Disease, Diabetes, Medical Report Analysis, Explainable AI, Health Monitoring, Decision Support System},
        month = {May},
        }