Generative AI in medicine: A thorough examination of applications, challenges, and future perspectives

Generative AI, an artificial intelligence, significantly transforms the healthcare sector. Recent breakthroughs in Generative AI include the use of language models and leveraging modern pre-trained Transformer models such as ChatGPT, Bard, LLaMA, DALL-E, and Bing. In medical applications, the advent of Large Language Models (LLMs) is a significant tool for predicting diseases, identifying risk factors, and enhancing diagnostic accuracy by analyzing a massive volume of unevenly distributed medical resources. This study provides a comprehensive review of existing literature on the use of LLMs in healthcare. It elucidates the 'status quo' of language models for general readers, healthcare professionals, and researchers. Specifically, this study investigates the capabilities of LLMs, including the transformation of healthcare consultation, enhancement of patient management and treatment, evolution of medical education, optimal resource utilization, and advancement of clinical research. The article organizes the literature based on human organs that will help readers quickly find relevant LLM applications for specific medical fields. The outcome of this survey will help medical professionals, researchers, and the healthcare industry understand the benefits, challenges, observed limitations, future challenges and applications of LLMs in healthcare.