This study proposes a method for generating complex and long-horizon off-line task plans using large language models (LLMs). Although several studies have been conducted in recent years on robot task planning using LLMs, the planning results tend to ...
Vision-Language Models (VLMs) are regarded as efficient paradigms that build a bridge between visual perception and textual interpretation. For medical visual tasks, they can benefit from expert observation and physician knowledge extracted from text...
ObjectiveTo assess the accuracy, completeness, and reproducibility of Large Language Models (LLMs) (Copilot, GPT-3.5, and GPT-4) on antimalarial use in systemic lupus erythematosus (SLE).Materials and MethodsWe utilized 13 questions derived from pati...
Neural networks : the official journal of the International Neural Network Society
Feb 25, 2025
In the domain of Few-shot Relation Extraction (FSRE), the primary objective is to distill relational facts from limited labeled datasets. This task has recently witnessed significant advancements through the integration of Pre-trained Language Models...
BackgroundMost common forms of dementia, including Alzheimer's disease, are associated with alterations in spoken language.ObjectiveThis study explores the potential of a speech-based machine learning (ML) approach in estimating cognitive impairment,...
INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large language models (LLMs), for synthesizing information in a simulated randomized clinical trial (RCT) for an anti-seizure medication, cenobamate, demon...
BACKGROUND: Cognitive assessment is an important component of applied psychology, but limited access and high costs make these evaluations challenging.
INTRODUCTION: This paper introduces an intelligent question-answering system designed to deliver personalized medical information to diabetic patients. By integrating large language models with knowledge graphs, the system aims to provide more accura...
Scandinavian journal of clinical and laboratory investigation
Feb 19, 2025
Large language models (LLMs) have demonstrated high performance across various fields due to their ability to understand, generate, and manipulate human language. However, their potential in specialized medical domains, such as clinical chemistry and...
OBJECTIVE: The Functional Seizures Likelihood Score (FSLS) is a supervised machine learning-based diagnostic score that was developed to differentiate functional seizures (FS) from epileptic seizures (ES). In contrast to this targeted approach, large...