AIMC Topic: Large Language Models

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MedKA: A knowledge graph-augmented approach to improve factuality in medical Large Language Models.

Journal of biomedical informatics
Large language models (LLMs) have demonstrated remarkable potential in medical applications. However, they still face critical challenges such as hallucinations, knowledge inconsistency, and insufficient integration of domain-specific medical experti...

Toward Cross-Hospital Deployment of Natural Language Processing Systems: Model Development and Validation of Fine-Tuned Large Language Models for Disease Name Recognition in Japanese.

JMIR medical informatics
BACKGROUND: Disease name recognition is a fundamental task in clinical natural language processing, enabling the extraction of critical patient information from electronic health records. While recent advances in large language models (LLMs) have sho...

Psychometric Evaluation of Large Language Model Embeddings for Personality Trait Prediction.

Journal of medical Internet research
BACKGROUND: Recent advancements in large language models (LLMs) have generated significant interest in their potential for assessing psychological constructs, particularly personality traits. While prior research has explored LLMs' capabilities in ze...

Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation.

Scientific reports
The substantial increase in mental health disorders globally necessitates scalable, accurate tools for detecting and classifying these conditions in digital environments. This study addresses the critical challenge of automated mental health classifi...

A Large Language Model-Powered Map of Metabolomics Research.

Analytical chemistry
We present a comprehensive map of the metabolomics research landscape, synthesizing insights from over 80,000 publications. Using PubMedBERT, we transformed abstracts into 768-dimensional embeddings that capture the nuanced thematic structure of the ...

Exploring the potential of lightweight large language models for AI-based mental health counselling task: a novel comparative study.

Scientific reports
In recent years, Transformer-based large language models (LLMs) have significantly improved upon their text generation capability. Mental health is a serious concern that can be addressed using LLM-based automated mental health counselors. These syst...

Quality assessment of large language models' output in maternal health.

Scientific reports
Optimising healthcare is linked to broadening access to health literacy in Low- and Middle-Income Countries. The safe and responsible deployment of Large Language Models (LLMs) may provide accurate, reliable, and culturally relevant healthcare inform...

Cognition-enhanced geospatial decision framework integrating fuzzy FCA, surprisingly popular method, and a large language model.

Scientific reports
This study introduces a cognition-enhanced framework for geospatial decision-making by integrating Fuzzy Formal Concept Analysis (FCA), the Surprisingly Popular (SP) method, and a Large Language Model (GPT-4o). Our approach captures cognitive influen...

Exploring the possibilities and limitations of customized large language model to support and improve cervical cancer screening.

BMC medical informatics and decision making
BACKGROUND: The rapid advancement of artificial intelligence, driven by Generative Pre-trained Transformers (GPT), has transformed natural language processing. Prompt engineering plays a key role in guiding model outputs effectively. Our primary obje...

Large language models versus traditional textbooks: optimizing learning for plastic surgery case preparation.

BMC medical education
BACKGROUND: Large language models (LLMs), such as ChatGPT-4 and Gemini, represent a new frontier in surgical education by offering dynamic, interactive learning experiences. Despite their potential, concerns about the accuracy, depth of knowledge, an...