Purpose To evaluate the impact of domain adaptation on the performance of language
models in predicting five-point Deauville scores on the basis of clinical fluorine 18 …

Conclusion When interpreting promising findings from LLM-related studies, it is crucial to
also account for their limitations. LLMs' tendency to hallucinate, their lack of transparency …

Background The automatic generation of radiology reports, which seeks to create a free-text
description from a clinical radiograph, is emerging as a pivotal intersection between clinical …

The development of large language models (LLMs) is a recent success in the field of
generative artificial intelligence (AI). They are computer models able to perform a wide …

Natural Language Processing (NLP) has gained prominence in diagnostic radiology,
offering a promising tool for improving breast imaging triage, diagnosis, lesion …

Rapid growth in adoption of electronic health records (EHRs) has led to an unprecedented
expansion in the availability of large longitudinal datasets. Large initiatives such as the …

Background Automated language analysis of radiology reports using natural language
processing (NLP) can provide valuable information on patients' health and disease. With its …

Large language models (LLMs) have recently demonstrated their potential in clinical
applications, providing valuable medical knowledge and advice. For example, a large dialog …

The introduction of large language models (LLMs) into clinical practice promises to improve
patient education and empowerment, thereby personalizing medical care and broadening …

Abstract Importance Large language models (LLMs) like OpenAI's ChatGPT are powerful
generative systems that rapidly synthesize natural language responses. Research on LLMs …