Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
"Comparative analysis of large language models against the NHS 111 online triaging for emergency ophthalmology".
Eye (Lond)
January 2025
Ophthalmology Department, Norfolk & Norwich University Hospital, Norwich, UK.
Background: This study presents a comprehensive evaluation of the performance of various large language models in generating responses for ophthalmology emergencies and compares their accuracy with the established United Kingdom's National Health Service 111 online system.
Methods: We included 21 ophthalmology-related emergency scenario questions from the NHS 111 triaging algorithm. These questions were based on four different ophthalmology emergency themes as laid out in the NHS 111 algorithm.
Use of ChatGPT to Generate Informed Consent for Surgery in Urogynecology.
Urogynecology (Phila)
January 2025
From the Division of Urogynecology, Walter Reed National Military Medical Center, Bethesda, MD.
Importance: Use of the publicly available Large Language Model, Chat Generative Pre-trained Transformer (ChatGPT 3.5; OpenAI, 2022), is growing in health care despite varying accuracies.
Objective: The aim of this study was to assess the accuracy and readability of ChatGPT's responses to questions encompassing surgical informed consent in urogynecology.
Introduction: Simulation has become an integral part of healthcare education. Studies demonstrate rapid knowledge and skill acquisition with the use of simulation and rapid knowledge degradation if it is not further reinforced. Effect of simulation on metacognitive processes, or the ability to understand one's own knowledge, is not well-investigated yet.
View Article and Find Full Text PDFA case report: spleen Epstein-Barr virus-positive inflammatory follicular dendritic cell sarcoma.
J Gastrointest Oncol
December 2024
Department of Radiology, Zhuhai Clinical Medical College of Jinan University (Zhuhai People's Hospital, The Affiliated Hospital of Beijing Institute of Technology), Jinan University, Zhuhai, China.
Background: Epstein-Barr virus-positive (EBV) inflammatory follicular dendritic cell sarcoma (IFDCS) is a rare stroma-derived neoplasm of lymphoid tissues. It typically involves the spleen and liver, and is often associated with the presence of EBV. Because of its nonspecific clinical and imaging findings, making a correct diagnosis at the time of initial diagnosis is challenging.
View Article and Find Full Text PDFA Multianalyte Machine Learning Model to Detect Wrong Blood in Complete Blood Count Tube Errors in a Pediatric Setting.
Clin Chem
January 2025
Department of Pathology and Laboratory Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, United States.
Background: Multianalyte machine learning (ML) models can potentially identify previously undetectable wrong blood in tube (WBIT) errors, improving upon current single-analyte delta check methodology. However, WBIT detection model performance has not been assessed in a real-world, low-prevalence context. To estimate real-world positive predictive values, we propose a methodology to assess WBIT detection models by evaluating the impact of missing data and by using a "low prevalence" validation data set.
View Article and Find Full Text PDFWant 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!