LLMs in healthcare

Abstract

This paper explores the integration of Large Language Models (LLMs), in the healthcare domain, focusing on improving accessibility, medication management, and public health awareness. The research investigates the transformative role of LLMs in natural language processing and their application in healthcare, highlighting their potential to enhance patient-doctor communication, medical documentation, and research. We conducted comprehensive user studies, literature reviews, and interviews with two key user groups: medical professionals and general users familiar with LLMs. The objectives include advancing telemedicine, providing preliminary diagnoses, enhancing drug information clarity, and understanding medical documentation through NLP and image recognition. A human-centred AI approach underscores the project's emphasis on ethical compliance and data security. In-depth user studies reveal the perspectives of healthcare professionals and the general public on LLM integration in healthcare, identifying benefits, challenges, and ethical considerations. Preliminary findings highlight the utility of ChatGPT in academia and research, diagnostic assistance, and ethical concerns, suggesting its role as a supplementary tool in healthcare. The study concludes with a cautious yet optimistic outlook on the integration of ChatGPT and similar models in healthcare, emphasizing the need for enhancements in reliability, ethical compliance, and fostering trust among users.