The Challenges of ChatGPT in Healthcare Scientific Writing

Abstract

Due to the increase in artificial intelligence (AI) applications in various fields of healthcare (1), ChatGPT, as one of the branches of AI, is used for writing scientific texts.In addition to its capabilities and advantages, ChatGPT also faces certain challenges and limitations.The authors aimed to provide evidence in this letter.ChatGPT, powered by the generative pre-trained transformer 3.5 architecture, was introduced by OpenAI on November 30, 2022 (2).The advent of OpenAI's large language models began with GPT-1 in 2017, followed by GPT-2 and GPT-3, and finally the well-known ChatGPT (3).ChatGPT's main purpose was to produce human-like text responding to user inputs.Using a vast dataset gathered from various sources, ChatGPT acquired extensive knowledge spanning a wide range of topics up until its last update in September 2021.Despite chatbots and conversational agents being utilized in the medical field, it was only after the introduction of ChatGPT that the potential of chatbots was fully revealed (4).ChatGPT is a valuable tool for various tasks in the medical field, such as extracting information from medical records, aiding in literature searches by finding academic papers and extracting key findings from them, emphasizing areas of uncertainty, and providing suggestions for structure (5).Moreover, its capabilities are evident as it can achieve acceptable scores on the United States medical licensing exam (USMLE) (6).Additionally, ChatGPT can generate abstracts that, in certain cases, resemble those produced by humans, making it a valuable resource for medical professionals and researchers (7).ChatGPT, similar to other chatbots, depends on machine learning, particularly deep learning and natural

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