Publication

Abstract : In the dynamic realm of healthcare, accurate disease prediction stands as a cornerstone for proactive management and personalized care. Through the introduction of Unified Medical Identification (UMI), users can easily connect to their medical records anywhere at any time. With advanced features like rural language support via video-based disease prediction integrated with the Large Language Model, the system generates a broader bracket of users. An ensembled machine learning model is used for general disease prediction. Integrating the CatBoost Classifier with the LangChain framework, the model accurately detects chronic diseases keeping UMI as the central source of the user’s medical data. Furthermore, an AI chatbot aids in the enhancement of user engagement offering targeted treatment options and suitable lifestyle recommendations resulting in better health outcomes. With a remarkable 92.8% accuracy in general disease prediction and a whopping 95.8% accuracy in chronic disease prediction, this revolutionary tool not only reforms the healthcare delivery mode but also guarantees that it is well accepted and widely available across dissimilar communities.