AIMC Topic: Large Language Models

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Exploring the potential of large language models to understand interpersonal emotion regulation strategies from narratives.

Emotion (Washington, D.C.)
Interpersonal emotion regulation involves using diverse strategies to influence others' emotions, commonly assessed with questionnaires. However, this method may be less effective for individuals with limited literacy or introspection skills. To addr...

Use of Open-Source Large Language Models for Automatic Synthesis of the Entire Imaging Medical Records of Patients: A Feasibility Study.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVES: Reviewing the entire history of imaging exams of a single patient's records is an essential step in clinical practice, but it is time and resource consuming, with potential negative effects on workflow and on the quality of med...

Unveiling the Potential of Large Language Models in Transforming Chronic Disease Management: Mixed Methods Systematic Review.

Journal of medical Internet research
BACKGROUND: Chronic diseases are a major global health burden, accounting for nearly three-quarters of the deaths worldwide. Large language models (LLMs) are advanced artificial intelligence systems with transformative potential to optimize chronic d...

Accuracy, consistency, and contextual understanding of large language models in restorative dentistry and endodontics.

Journal of dentistry
OBJECTIVE: This study aimed to evaluate and compare the performance of several large language models (LLMs) in the context of restorative dentistry and endodontics, focusing on their accuracy, consistency, and contextual understanding.

International Symposium on Ruminant Physiology: Leveraging computer vision, large language models, and multimodal machine learning for optimal decision making in dairy farming.

Journal of dairy science
This article explores various applications of artificial intelligence (AI) technologies in dairy farming, including the use of computer vision systems (CVS) for animal identification, BCS and body shape analysis, and potential uses of large language ...

Detecting implicit biases of large language models with Bayesian hypothesis testing.

Scientific reports
Despite the remarkable performance of large language models (LLMs), such as generative pre-trained Transformers (GPTs), across various tasks, they often perpetuate social biases and stereotypes embedded in their training data. In this paper, we intro...

Evaluating the Effectiveness of Large Language Models in Providing Patient Education for Chinese Patients With Ocular Myasthenia Gravis: Mixed Methods Study.

Journal of medical Internet research
BACKGROUND: Ocular myasthenia gravis (OMG) is a neuromuscular disorder primarily affecting the extraocular muscles, leading to ptosis and diplopia. Effective patient education is crucial for disease management; however, in China, limited health care ...

Large Language Models in Biochemistry Education: Comparative Evaluation of Performance.

JMIR medical education
BACKGROUND: Recent advancements in artificial intelligence (AI), particularly in large language models (LLMs), have started a new era of innovation across various fields, with medicine at the forefront of this technological revolution. Many studies i...

Towards accurate differential diagnosis with large language models.

Nature
A comprehensive differential diagnosis is a cornerstone of medical care that is often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures. Interactive interfaces p...

Extracting Pulmonary Embolism Diagnoses From Radiology Impressions Using GPT-4o: Large Language Model Evaluation Study.

JMIR medical informatics
BACKGROUND: Pulmonary embolism (PE) is a critical condition requiring rapid diagnosis to reduce mortality. Extracting PE diagnoses from radiology reports manually is time-consuming, highlighting the need for automated solutions. Advances in natural l...