Developing a system based on Chabot for detecting Epidemics in educational institution

This study presents an intelligent Chabot system powered by Artificial Intelligence (AI) techniques, including GPT-based natural language processing (NLP), designed to predict potential diseases and analyze symptom overlap based on user inputs. The Chabot interprets symptoms entered by users and offers a probabilistic diagnosis that outlines the likelihood of multiple diseases, inclusive of health guidance. In the cases above, the results of expert evaluations came up with very high satisfaction regarding the overall performance of the Chabot: most physicians and specialists said that the system gave only accurate, user-friendly, and efficient data for getting reliable diagnostic information. Besides, the Chabot design makes the identification of data faster and provides support for effective diagnostic protocols; thus, a device highly useful for medical diagnostics and epidemic management is developed, reaching an accuracy rate of as much as 97.5% compared to expert assessment.