Detecting Pneumonia and COVID-19 by Using Chest X-Ray with ResNet Algorithm

This paper centres on the development of a health-care application or website that leverages AI-driven medical analysis that will transform patient care and diagnosis. The initial goal of this project is to improve the usability and quality of medical assessments simultaneously by effectively utilizing the algorithmic capabilities of artificial intelligence. This effort aims to point out specific challenges including but not limited to inaccurate diagnoses and restricted access to personalized healthcare services. The paper encompasses several key phases, such as data acquisition, algorithm creation, equipping users, validating the clinical efficacy, and addressing ethical issues. The underlying concept of the given platform guarantees rapid and precise diagnostics, personalized views into the matter, and strict upholding to ethical and privacy standards. Through the acceleration of medical discoveries, optimization of treatment options, and the promotion of healthier outcomes as the standard of care, the program aspires to shape a future in which healthcare research, decision-making, and outcomes are elevated to new heights complying with the Sustainable Development Goal SDG-3. The proposed data set has been chosen from kaggle and the presented work has been carried through ResNetAlgorithm. The obtained result shows its efficiency of accuracy of 95.14% and sensitivity and specificity as 96% which is better than the existing art of literature.