This paper presents an analysis of the advantages, limitations, ethical considerations, future prospects, and practical applications of ChatGPT and artificial intelligence (AI) in the healthcare and medical domains. ChatGPT is an advanced language model that uses deep learning techniques to produce human-like responses to natural language inputs. It is part of the family of generative pre-training transformer (GPT) models developed by OpenAI and is currently one of the largest publicly available language models. ChatGPT is capable of capturing the nuances and intricacies of human language, allowing it to generate appropriate and contextually relevant responses across a broad spectrum of prompts. The potential applications of ChatGPT in the medical field range from identifying potential research topics to assisting professionals in clinical and laboratory diagnosis. Additionally, it can be used to help medical students, doctors, nurses, and all members of the healthcare fraternity to know about updates and new developments in their respective fields. The development of virtual assistants to aid patients in managing their health is another important application of ChatGPT in medicine. Despite its potential applications, the use of ChatGPT and other AI tools in medical writing also poses ethical and legal concerns. These include possible infringement of copyright laws, medico-legal complications, and the need for transparency in AI-generated content. In conclusion, ChatGPT has several potential applications in the medical and healthcare fields. However, these applications come with several limitations and ethical considerations which are presented in detail along with future prospects in medicine and healthcare.

BackgroundChatbots are computer programs that use artificial intelligence (AI) and natural language processing (NLP) to simulate conversations with humans. One such chatbot is ChatGPT, which uses the third-generation generative pre-trained transformer (GPT-3) developed by OpenAI. ChatGPT has been praised for its ability to generate text, but concerns have been raised about its accuracy and precision in generating data, as well as legal issues related to references. This study aims to investigate the frequency of AI hallucination in research proposals entirely drafted by ChatGPT. MethodologyAn analytical design was employed to investigate AI hallucination by ChatGPT. A total of 178 references listed by ChatGPT were verified for inclusion in the study. Statistical analysis was performed by five researchers who entered their data into a Google Form, and the final results were represented using pie charts and tables. ResultsOut of the 178 references analyzed, 69 references did not have a Digital Object Identifier (DOI), and 28 references neither turned up on Google search nor had an existing DOI. Three references were listed from books and not research articles. These observations suggest that ChatGPT's ability to generate reliable references for research topics may be limited by the availability of DOI and the accessibility of online articles. ConclusionsThe study highlights the potential limitations of ChatGPT's ability to generate reliable references for research proposals. AI hallucination is a problem that may negatively impact decision-making and may give rise to ethical and legal problems. Improving the training inputs by including diverse, accurate, and contextually relevant data sets along with frequent updates to the training models could potentially help address these issues. However, until these issues are addressed, researchers using ChatGPT should exercise caution in relying solely on the references generated by the AI chatbot.

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