In this preview, we highlight what we believe to be the major contributions of the review and discuss opportunities to build on the work, including by closely examining the incentive structures that contribute to our dataset culture and by further engaging with other disciplines.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600242 | PMC |
| http://dx.doi.org/10.1016/j.patter.2021.100388 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Dementia Care Research and Psychosocial Factors.
Alzheimers Dement
December 2024
NYU Langone Health, New York, NY, USA.
Background: Large language models (LLMs) provide powerful natural language processing capabilities in medical and clinical tasks. Evaluating LLM performance is crucial due to potential false results. In this study, we assessed ChatGPT and Llama2, two state-of-the-art LLMs, in extracting information from clinical notes, focusing on cognitive tests, specifically the Mini Mental State Exam (MMSE) and Cognitive Dementia Rating (CDR).
View Article and Find Full Text PDFHealth and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study.
Diagnostics (Basel)
December 2024
Centre for Nutrition Research, Department of Nutrition, Food Science, Physiology and Toxicology, University of Navarra, 31009 Pamplona, Spain.
Introduction: Glucose homeostasis may be dependent on liver conditions and influence health-related markers and quality of life (QoL) objective measurements. This study aimed to analyze the interactions of glycemia with liver and health status in a prediabetic population.
Subjects And Methods: This study included 2220 overweight/obese prediabetics from the multinational PREVIEW project.
The Transformative Potential of Large Language Models in Mining Electronic Health Records Data: Content Analysis.
JMIR Med Inform
January 2025
Servicio Oncologia Radioterápica, Hospital Universitario Virgen Macarena, Andalusian Health Service, Seville, Spain.
Background: In this study, we evaluate the accuracy, efficiency, and cost-effectiveness of large language models in extracting and structuring information from free-text clinical reports, particularly in identifying and classifying patient comorbidities within oncology electronic health records. We specifically compare the performance of gpt-3.5-turbo-1106 and gpt-4-1106-preview models against that of specialized human evaluators.
View Article and Find Full Text PDFMulticriteria assessment of optical coherence tomography using non-raster trajectories.
J Microsc
December 2024
Université de Franche-Comté, CNRS, AS2M Department, FEMTO-ST Institute, Besançon, France.
This article presents a qualitative, quantitative, and experimental analysis of optical coherence tomography (OCT) volumes obtained using different families of non-raster trajectories. We propose a multicriteria analysis to be used in the assessment of scan trajectories used in obtaining OCT volumetric point cloud data. The novel criteria includes exploitation/exploration ratio of the OCT data obtained, smoothness of the scan trajectory and fast preview of the acquired OCT data in addition to conventional criteria; time and quality (expressed as volume similarity rather than slice-by-slice image quality).
View Article and Find Full Text PDFAneRBC dataset: a benchmark dataset for computer-aided anemia diagnosis using RBC images.
Database (Oxford)
December 2024
School of Computing and Mathematical Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK.
Visual analysis of peripheral blood smear slides using medical image analysis is required to diagnose red blood cell (RBC) morphological deformities caused by anemia. The absence of a complete anaemic RBC dataset has hindered the training and testing of deep convolutional neural networks (CNNs) for computer-aided analysis of RBC morphology. We introduce a benchmark RBC image dataset named Anemic RBC (AneRBC) to overcome this problem.
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!