Abstract Purpose Large language models (LLMs) have demonstrated a level of competency
within the medical field. The aim of this study was to explore the ability of LLMs to predict the …

Abstract Objective Large Language Models (LLMs) have demonstrated proficiency in free-
text analysis in healthcare. With recent advancements, GPT-4 now has the capability to …

In this study we uncover the unexpected efficacy of residual-based large language models
(LLMs) as part of encoders for biomedical imaging tasks a domain traditionally devoid of …

Objectives: Owing to the rapid progress of natural language processing (NLP), the role of
NLP in the medical field has radically gained considerable attention from both NLP and …

Radiology has usually been the field of medicine that has been at the forefront of
technological advances, often being the first to wholeheartedly embrace them. Whether it's …

Recent advances in AI combine large language models (LLMs) with vision encoders that
bring forward unprecedented technical capabilities to leverage for a wide range of …

To the Editor, We read with great interest the article by Javan et al., published in the May
2023 issue of CardioVascular and Interventional Radiology, which assessed ChatGPT's …

There has been substantial press recently regarding the impressive performance of large
language models (LLM), particularly the OpenAI tool “Chat Generative Pre-Trained …

I read with great interest the study conducted by Nakaura et al., which investigates the
potential of Generative Pretrained Transformers (GPT) in generating radiology reports [1]. I …

We appreciate the interest in our study and the effort to provide general and valuable
insights on the potential of large language models (LLMs) on structured reporting [1, 2] …