large language models

A Real-World Evaluation of Large Language Model-Generated Hospital Courses in Pediatrics.

These findings support the use of LLM-generated hospital courses as starting drafts when paired with clinician review and institutional safeguards, and errors were common, but perceived potential harm was low, even assuming use without clinician correction.

M-AIDA: Meta-Analysis Intelligent Data Assistant

Research software for international-business meta-analysis: semi-automated effect-size extraction from academic PDFs through a vendor-neutral large-language-model adapter, human-in-the-loop verification by the principal investigator, and an immutable data-lock workflow that exports a reproducible effect-size dataset fo...

AI-Driven IoT (AIIOT) in Brain Health Study

Context and Justification The prevalence of neurodegenerative diseases around the world demands a paradigm change from reactive, episodic clinical diagnosis to ongoing, proactive neuro-monitoring. The possibility for early detection and individualized management is limited by the fact that traditional diagnostic techni...

Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination

G-Frame, an adaptive multi-agent framework integrating Bayesian and team game principles, establishes an automated closed-loop for high-quality data synthesis and model training and synthesizes a specialized corpus of 363,045 chains-of-thought and 199,589 question-answer pairs.

ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits

ViTAL-X, a lightweight model that equips frozen image-text backbones with temporal awareness while preserving their foundational spatial knowledge, achieves state-of-the-art performance and demonstrates that targeted, high-quality temporal alignment provides a highly efficient alternative to pure scaling.

Personality Without Persons? A Psychometric Critique of Big Five Testing in Large Language Models

It is demonstrated that Big Five inventories do not measure a construct equivalent to human personality in LLMs, highlighting the need for evaluation frameworks that are specifically designed and validated for LLMs, rather than transferring human psychological constructs without first establishing their validity.

Non-extensive statistics of the glioblastoma transcriptome: analysis code, derived results and validation-cohort inputs

Analysis code, derived result tables, figures and validation-cohort inputs for a study of non-extensive (Tsallis) statistics in the glioblastoma transcriptome. Expression deviations of each sample are fitted with q-Gaussian laws by maximum likelihood. In a longitudinal GLASS cohort (230 libraries from 115 IDH-wildtype...

A Survey on Table Mining with Large Language Models: Challenges, Advancements and Prospects

This survey conducts a comprehensive review of the literature on table mining with Large Language Models, exploring the challenges unique to this domain, such as heterogeneous table structures, contextual ambiguity, and domain-specific knowledge requirements.

Evaluating Large Language Models for Triple Extraction from Chinese Historical Geographic Sources: A Case Study Using Sources from the China Historical GIS Project

Multimodal medical diagnosis: a mini review of LLM–vision fusion models in low-resource healthcare settings

Recent advances in large language models (LLMs) and vision transformers have enabled multimodal systems that integrate clinical text with medical imaging for diagnostic decision-making. While these systems show promising results on benchmark datasets in well-resourced research settings, their applicability in low-resou...

What clinicians should know about how large language models reason

Phase-Based Dynamic Prediction of Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: Comparison of a Large Language Model with Intensive Care Specialists

Background and Objectives: Delayed cerebral ischemia (DCI) is a major determinant of poor outcome after aneurysmal subarachnoid hemorrhage (aSAH), yet early risk prediction remains difficult, particularly in sedated or ventilated intensive care patients. We evaluated whether a large language model (LLM) could predict D...