AIMC Topic: Large Language Models

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Prompt architecture induces methodological artifacts in large language models.

PloS one
We examine how the seemingly arbitrary way a prompt is posed, which we term "prompt architecture," influences responses provided by large language models (LLMs). Five large-scale, full-factorial experiments performing standard (zero-shot) similarity ...

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...

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 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...

Ontology accelerates few-shot learning capability of large language model: A study in extraction of drug efficacy in a rare pediatric epilepsy.

International journal of medical informatics
OBJECTIVE: Dravet Syndrome (DS) is a developmental and epileptic encephalopathy that is characterized by severe, prolonged motor seizures and high resistance to multiple antiseizure medications (ASMs) with multiple comorbidities. Evaluating the effic...

Industrial applications of large language models.

Scientific reports
Large language models (LLMs) are artificial intelligence (AI) based computational models designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate language patterns, enabling remark...

DrugGen enhances drug discovery with large language models and reinforcement learning.

Scientific reports
Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials. Deep learning advancements, particularly generative models, offer potential solutions...

Arch-Eval benchmark for assessing chinese architectural domain knowledge in large language models.

Scientific reports
The burgeoning application of Large Language Models (LLMs) in Natural Language Processing (NLP) has prompted scrutiny of their domain-specific knowledge processing, especially in the construction industry. Despite high demand, there is a scarcity of ...