Download full-text PDF

Source
http://dx.doi.org/10.1186/s12879-025-10475-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773754PMC

Publication Analysis

Top Keywords

correction impact
4
impact age
4
age comparative
4
comparative diagnostic
4
diagnostic accuracy
4
accuracy temporal
4
temporal artery
4
artery thermometers
4
thermometers non-contact
4
non-contact infrared
4

Similar Publications

Purpose: To explore the perceived utility and effect of simplified radiology reports on oncology patients' knowledge and feasibility of large language models (LLMs) to generate such reports.

Materials And Methods: This study was approved by the Institute Ethics Committee. In phase I, five state-of-the-art LLMs (Generative Pre-Trained Transformer-4o [GPT-4o], Google Gemini, Claude Opus, Llama-3.

View Article and Find Full Text PDF

Background: Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. One way to assess this heterogeneity is to look for patterns in the subphenotype data.

View Article and Find Full Text PDF

Purpose: The positron range effect can impair PET image quality of Gallium-68 (Ga). A positron range correction (PRC) can be applied to reduce this effect. In this study, the effect of a tissue-independent PRC for Ga was investigated on patient data.

View Article and Find Full Text PDF

Background And Objectives: Three-column osteotomy (3CO) offers substantial spinal deformity correction. Thoracic neurovascular bundle sacrifice is often required, and anterior spinal artery (ASA) perfusion can be compromised. Spinal angiography allows localization of variable ASA vascular contribution.

View Article and Find Full Text PDF

Use of ChatGPT Large Language Models to Extract Details of Recommendations for Additional Imaging From Free-Text Impressions of Radiology Reports.

AJR Am J Roentgenol

January 2025

Center for Evidence-Based Imaging, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, 1620 Tremont Street, Boston, MA 02120 Phone: 617-525-9702.

Automated extraction of actionable details of recommendations for additional imaging (RAIs) from radiology reports could facilitate tracking and timely completion of clinically necessary RAIs and thereby potentially reduce diagnostic delays. To assess the performance of large-language models (LLMs) in extracting actionable details of RAIs from radiology reports. This retrospective single-center study evaluated reports of diagnostic radiology examinations performed across modalities and care settings within five subspecialties (abdominal imaging, musculoskeletal imaging, neuroradiology, nuclear medicine, thoracic imaging) in August 2023.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!