Comment on: ChatGPT: Chasing the Storm in Radiology Training and Education
Abstract
Letter to: ChatGPT: Chasing the Storm in Radiology Training and Education Indian J Radiol Imaging 2023; 33(04): 431-435 DOI: 10.1055/s-0043-1774743 ChatGPT: Chasing the Storm in Radiology Training and Education We carefully reviewed the editorial penned by Sodhi et al, addressing the potential application of Chat Generative Pre-Trained Transformer (ChatGPT) in training and educating radiology residents, coupled with a prudent acknowledgment of its limitations and pitfalls.[ 1 ] In response, we aim to contribute some perspectives on large language models (LLMs) in radiology, from our experience of utilizing and evaluating various open-source and proprietary LLMs for various tasks in radiology. In their editorial, the authors exclusively leveraged ChatGPT, a widely recognized and freely available LLM. It is noteworthy that while the free version of ChatGPT utilizes the GPT-3.5 model, the paid version, ChatGPT Plus and Team, leverages the GPT-4 model that boasts three key features: enhanced creativity, compatibility with visual input, and an ability to process longer contexts. GPT-4 offers unparalleled capabilities in tasks demanding advanced reasoning and complex instruction comprehension[ 2 ] and also has the ability to retrieve information from the Internet real time using retrieval augmented generation.[ 3 ] Drawing from our personal experiences, Microsoft Bing Chat, now rebranded as Copilot, emerges as a viable alternative, allowing the utilization of the advanced GPT-4…
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