DiseaseGPT: Leveraging Large Language Models for Symptom Elaboration and Healthcare Communication

This paper examines the use of Large Language Models (LLMs) in healthcare, focusing on the development of a system called DiseaseGPT. DiseaseGPT aims to enhance the interaction between healthcare professionals and patients by providing clear and comprehensive explanations of symptoms for a wide range of medical conditions. The system leverages the advanced capabilities of LLMs to break down complex medical language, making it more accessible for patients and improving overall communication. The paper explores the technical architecture and deployment of DiseaseGPT as a web application, outlining the model's training, data handling, and integration into healthcare workflows. Additionally, the paper evaluates the potential benefits of DiseaseGPT, including improved diagnostic accuracy, enhanced patient education, and its role in supporting medical decision-making. We also discuss key challenges, such as data privacy concerns, ethical considerations, and the limitations of AI in healthcare. Finally, the paper offers insights into the future of AI in the medical field, highlighting how DiseaseGPT represents an important step in addressing communication gaps, personalizing care, and aiding in the early identification and treatment of diseases. The research underscores the potential of AI to transform both clinical practice and patient outcomes.