AI-Powered Symptom Checker and Risk Assessment Web Application for Tuberculosis (TB)

Tuberculosis remains among the greatest public health challenges, especially in developing countries where lack of early diagnosis due to limited access results in late treatment and increased transmission. Rapid advances in Artificial Intelligence and Natural Language Processing bring forth digital health tools as strong solutions in preliminary symptom assessment and risk evaluation. This paper provides an overview of the current landscape on AI-based TB detection systems, prevailing gaps in the digital health solution space, and an AI-driven web application capable of analyzing symptoms, vitals, and risk factors based on conversational inputs. It assessed how such platforms could contribute to enhancing conventional workflows of healthcare by providing timely advice, raising awareness, and improving access in resource-poor settings. Further development could include the use of imaging-based diagnostics, extending multilingual capabilities, and further developing models of AI that could work offline in rural environments.