AIMC Topic: Language

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The role of artificial intelligence in medical education: an evaluation of Large Language Models (LLMs) on the Turkish Medical Specialty Training Entrance Exam.

BMC medical education
OBJECTIVE: To evaluate the performance of advanced large language models (LLMs)-OpenAI-ChatGPT 4, Google AI-Gemini 1.5 Pro, Cohere-Command R + and Meta AI-Llama 3 70B on questions from the Turkish Medical Specialty Training Entrance Exam (2021, 1st s...

TMNRED, A Chinese Language EEG Dataset for Fuzzy Semantic Target Identification in Natural Reading Environments.

Scientific data
Semantic understanding is central to advanced cognitive functions, and the mechanisms by which the brain processes language information are still being explored. Existing EEG datasets often lack natural reading data specific to Chinese, limiting rese...

Comparing Diagnostic Accuracy of Clinical Professionals and Large Language Models: Systematic Review and Meta-Analysis.

JMIR medical informatics
BACKGROUND: With the rapid development of artificial intelligence (AI) technology, especially generative AI, large language models (LLMs) have shown great potential in the medical field. Through massive medical data training, it can understand comple...

Evaluating ChatGPT in Qualitative Thematic Analysis With Human Researchers in the Japanese Clinical Context and Its Cultural Interpretation Challenges: Comparative Qualitative Study.

Journal of medical Internet research
BACKGROUND: Qualitative research is crucial for understanding the values and beliefs underlying individual experiences, emotions, and behaviors, particularly in social sciences and health care. Traditionally reliant on manual analysis by experienced ...

Evaluating Large Language Model's accuracy in current procedural terminology coding given operative note templates across various plastic surgery sub-specialties.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
BACKGROUND: Manual CPT coding from operative notes is a time-intensive process that adds to the administrative burden in healthcare. Large Language Models (LLMs) offer a promising solution, but their accuracy in assigning CPT codes based on full oper...

Harnessing genotype and phenotype data for population-scale variant classification using large language models and bayesian inference.

Human genetics
Variants of Uncertain Significance (VUS) in genetic testing for hereditary diseases burden patients and clinicians, yet clinical data that could reduce VUS are underutilized due to a lack of scalable strategies. We assessed whether a machine learning...

Randomized Controlled Study on the Impact of Problem-Based Learning Combined With Large Language Models on Critical Thinking Skills in Nursing Students.

Nurse educator
BACKGROUND: The integration of Large Language Models (LLMs) into nursing education presents a novel approach to enhancing critical thinking skills. This study evaluated the effectiveness of LLM-assisted Problem-Based Learning (PBL) compared to tradit...

Fine-tune language models as multi-modal differential equation solvers.

Neural networks : the official journal of the International Neural Network Society
In the growing domain of scientific machine learning, in-context operator learning has shown notable potential in building foundation models, as in this framework the model is trained to learn operators and solve differential equations using prompted...

SpikeCLIP: A contrastive language-image pretrained spiking neural network.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) have emerged as a promising alternative to conventional Artificial Neural Networks (ANNs), demonstrating comparable performance in both visual and linguistic tasks while offering the advantage of improved energy efficie...

DGPrompt: Dual-guidance prompts generation for vision-language models.

Neural networks : the official journal of the International Neural Network Society
Introducing learnable prompts into CLIP and fine-tuning them have demonstrated excellent performance across many downstream tasks. However, existing methods have insufficient interaction between modalities and neglect the importance of hierarchical c...