Personalized Symptom Analysis using Large Language Model

The need for intelligent healthcare systems gained momentum in recent years, with advancements in AI and machine-learning technologies. This paper develops all-inclusive AIbased healthcare assistant predicting diseases based on the symptoms reported by the user and then providing personalized health recommendations. This hybrid model, that is integrated with the OpenAI language model, enables the system to analyze patient symptoms, then give detailed customized descriptions of diseases, dietary recommendations, medication advice, workout plans, and precautions. It also finds the nearest hospitals for the disease diagnosis it has predicted to send the patients to get medical attention quickly. The real-world datasets of disease symptoms are used to test the performance of the system to ensure accuracy and reliability in health guidance. This system aims to enhance patient care and make the requisite health information more accessible for patients, leveraging advanced AI techniques to enable users in making proactive decisions regarding health and wellbeing.