Ali RazzaqMuhammad AhsanAbdullah Aayan Khundi2026-01-242026-01-242024https://escholar.umt.edu.pk/handle/123456789/18598This Final Year Project presents the development of an innovative web-based applicationdesigned for the intelligent analysis of healthcare symptoms using advanced machine learning techniques. The core of the project lies in the creation of a highly accurate machine learning model trained on a substantial dataset of patient symptoms and medicalrecords. This model employs state-of the-art algorithms to identify and diagnose various health conditions, demonstrating a significant level of precision and reliability. The project also focuses on the development of a user-friendly web interface that allows medical professionals, such as doctors and healthcare technicians, to input patient symptoms and receive immediate diagnostic results. The interface is designed to be intuitive, ensuring ease of use and clarity in the presentation of diagnostic information. Avital goal of this project is to enhance the efficiency of symptom analysis in the healthcare system, particularly in resource-limited settings. By providing a rapid and accurate diagnostic tool, the application aims to expedite patient treatment and improve overall healthcare outcomes. In addition, the project addresses the crucial aspects of datasecurity and patient privacy, ensuring that all user data and diagnostic results are handled with the utmost confidentiality and in compliance with healthcare regulations. The successful implementation of this project demonstrates the potential of combining digital data processing and machine learning in medical diagnostics. It not only contributes to the field of medical technology but also paves the way for future research and development in the application of artificial intelligence in healthcareenThesis