Rural communities often face critical challenges in accessing timely and accurate healthcare due to a shortage of medical professionals, limited diagnostic infrastructure, and geographical barriers. This paper presents the design and implementation of an AI-assisted multi-disease diagnosis system tailored for remote rural clinics, enabling frontline health workers to provide preliminary diagnostic support with minimal training.The proposed system integrates machine learning algorithms and rule-based expert systems to analyze symptoms, vital signs, and optional inputs such as medical images
Vidyalekshmi Chandrika (Thu,) studied this question.