AIMC Topic: Large Language Models

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The Evolution of Radiology Image Annotation in the Era of Large Language Models.

Radiology. Artificial intelligence
Although there are relatively few diverse, high-quality medical imaging datasets on which to train computer vision artificial intelligence models, even fewer datasets contain expertly classified observations that can be repurposed to train or test su...

Automated computation of the HEART score with the GPT-4 large language model.

The American journal of emergency medicine
BACKGROUND: Automated computation of the HEART score has the potential to facilitate clinical decision support and safety interventions. The goal of this study was to assess the performance of the GPT-4 large language model (LLM) in computation of th...

Dermacen analytica: A novel methodology integrating multi-modal large language models with machine learning in dermatology.

International journal of medical informatics
OBJECTIVE: To design, implement, evaluate, and quantify a novel and adaptable Artificial Intelligence-empowered methodology aimed at supporting a dermatologist's workflow in assessing and diagnosing skin conditions, leveraging AI's deep image analyti...

Using large language models as decision support tools in emergency ophthalmology.

International journal of medical informatics
BACKGROUND: Large language models (LLMs) have shown promise in various medical applications, but their potential as decision support tools in emergency ophthalmology remains unevaluated using real-world cases.

Comparative Analysis of Information Quality in Pediatric Otorhinolaryngology: Clinicians, Residents, and Large Language Models.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVE: Pediatric otorhinolaryngology (ORL) addresses complex conditions in children, requiring a tailored approach for patients and families. With artificial intelligence (AI) gaining traction in medical applications, this study evaluates the qua...

SAF: An action framework to self-check the Understanding Self-Consistency of Large Language Models.

Neural networks : the official journal of the International Neural Network Society
Large Language Models (LLMs), which are trained on massive text data, have demonstrated remarkable advancements in language understanding capabilities. Nevertheless, it remains unclear to what extent LLMs have effectively captured and utilized the im...

Evaluating the Accuracy, Reliability, Consistency, and Readability of Different Large Language Models in Restorative Dentistry.

Journal of esthetic and restorative dentistry : official publication of the American Academy of Esthetic Dentistry ... [et al.]
OBJECTIVE: This study aimed to evaluate the reliability, consistency, and readability of responses provided by various artificial intelligence (AI) programs to questions related to Restorative Dentistry.

SNIL: Generating Sports News From Insights With Large Language Models.

IEEE transactions on visualization and computer graphics
To enhance the appeal and informativeness of data news, there is an increasing reliance on data analysis techniques and visualizations, which poses a high demand for journalists' abilities. While numerous visual analytics systems have been developed ...

The dawn of a new era: can machine learning and large language models reshape QSP modeling?

Journal of pharmacokinetics and pharmacodynamics
Quantitative Systems Pharmacology (QSP) has emerged as a cornerstone of modern drug development, providing a robust framework to integrate data from preclinical and clinical studies, enhance decision-making, and optimize therapeutic strategies. By mo...