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Performance Evaluation and Implications of Large Language Models in Radiology Board Exams: Prospective Comparative Analysis.

JMIR medical education
BACKGROUND: Artificial intelligence advancements have enabled large language models to significantly impact radiology education and diagnostic accuracy.

The role of large language models in the peer-review process: opportunities and challenges for medical journal reviewers and editors.

Journal of educational evaluation for health professions
The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing...

A Comprehensive Analysis of a Social Intelligence Dataset and Response Tendencies Between Large Language Models (LLMs) and Humans.

Sensors (Basel, Switzerland)
In recent years, advancements in the interaction and collaboration between humans and have garnered significant attention. Social intelligence plays a crucial role in facilitating natural interactions and seamless communication between humans and Art...

Factors Associated With the Accuracy of Large Language Models in Basic Medical Science Examinations: Cross-Sectional Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) has become widely applied across many fields, including medical education. Content validation and its answers are based on training datasets and the optimization of each model. The accuracy of large language m...

Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND: This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education for men undergoing radiotherapy for localized prostate cancer, incorporating assessments from both clinicians and...

Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study.

JMIR medical informatics
BACKGROUND: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domai...

Enhancing semantical text understanding with fine-tuned large language models: A case study on Quora Question Pair duplicate identification.

PloS one
Semantical text understanding holds significant importance in natural language processing (NLP). Numerous datasets, such as Quora Question Pairs (QQP), have been devised for this purpose. In our previous study, we developed a Siamese Convolutional Ne...

The advantages of lexicon-based sentiment analysis in an age of machine learning.

PloS one
Assessing whether texts are positive or negative-sentiment analysis-has wide-ranging applications across many disciplines. Automated approaches make it possible to code near unlimited quantities of texts rapidly, replicably, and with high accuracy. C...

Evaluation of Multilingual Simplifications of IR Procedural Reports Using GPT-4.

Journal of vascular and interventional radiology : JVIR
This study assessed the feasibility of large language models such as GPT-4 (OpenAI, San Francisco, California) to summarize interventional radiology procedural reports to improve layperson understanding and translate medical texts into multiple langu...

Hybrid natural language processing tool for semantic annotation of medical texts in Spanish.

BMC bioinformatics
BACKGROUND: Natural language processing (NLP) enables the extraction of information embedded within unstructured texts, such as clinical case reports and trial eligibility criteria. By identifying relevant medical concepts, NLP facilitates the genera...