Clinical chemistry and laboratory medicine
Oct 27, 2025
OBJECTIVES: Large language models (LLMs), such as OpenAI's GPT-4o, have demonstrated considerable promise in transforming clinical decision support systems. In this study, we focused on a single but crucial task of clinical decision-making: laborator...
BACKGROUND: Ensuring appropriate use of CT scans is critical for patient safety and resource optimization. Decision support tools and artificial intelligence (AI), such as large language models (LLMs), have the potential to improve CT referral justif...
IEEE transactions on visualization and computer graphics
Oct 1, 2025
Large language models (LLMs) have gained widespread popularity due to their ability to perform ad-hoc natural language processing (NLP) tasks with simple natural language prompts. Part of the appeal for LLMs is their approachability to the general pu...
BACKGROUND: This study evaluates the use of large language models (LLMs) to analyze free-text responses from large-scale global health surveys, using data from the Enquête de Couverture Vaccinale (ECV) household coverage surveys from 2020, 2021, 2022...
AIM: To examine the implications of large language models (LLMs) in clinical documentation and explore strategies to preserve critical thinking among healthcare professionals in the age of artificial intelligence (AI).
Protein science : a publication of the Protein Society
Sep 1, 2025
Despite the vast number of enzymatic kinetic measurements reported across decades of biochemical literature, the majority of relational enzyme kinetic data-linking amino acid sequence, substrate identity, kinetic parameters, and assay conditions-rema...
This study investigates the application of ChatGPT-4 in extracting and classifying behavioral data from scientific literature, focusing on the daily time-activity budget of dairy cows. Accurate analysis of time-activity budgets is crucial for underst...
Recent advances in large language models (LLMs) enable domain-specific question answering using external knowledge. However, addressing information that is not included in training data remains a challenge, particularly in nuclear medicine, where exa...
BACKGROUND: Radiology reports are essential in medical imaging, providing critical insights for diagnosis, treatment, and patient management by bridging the gap between radiologists and referring physicians. However, the manual generation of radiolog...
BACKGROUND: Extracting clinical entities from unstructured medical documents is critical for improving clinical decision support and documentation workflows. This study examines the performance of various encoder and decoder models trained for Named ...
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