Smart Healthcare Assistant with Epidemiological Modelling

The perpetual threat posed by infectious disease outbreaks necessitates continuous advancements in epidemic modeling and public health interventions. Traditional approaches, while valuable, often face challenges in accurately predicting disease transmission dynamics and informing timely containment strategies. In response, this paper proposes a novel hybrid system that integrates established epidemiological models with cutting-edge Artificial Intelligence (AI) techniques, including ensemble methods and Generative Al for Natural Language Processing (NLP). This extends beyond epidemic modeling to address healthcare accessibility disparities through the development of a chatbot powered by Language Model (LLM) technology. The chatbot, capable of conversing in native languages, offers medical assistance and addresses health-related queries effectively, thereby bridging gaps in healthcare access. Additionally, sophisticated disease dynamic models and endemic simulators are employed to forecast disease spread accurately, ensuring the availability of healthcare information even in remote areas.