AIMC Topic: Natural Language Processing

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AI for Extracting Pre-Analytical Variability Data from Biomedical Literature: Feasibility and Validation.

Studies in health technology and informatics
INTRODUCTION: The quality and reproducibility of research results from biological samples are significantly influenced by the pre-analytical variability resulting from different conditions during sample collection, storage and processing. Although nu...

Prompting Is All You Need - Until It Isn't: Exploring the Limits of LLMs for Negation Detection in German Clinical Text.

Studies in health technology and informatics
INTRODUCTION: Detecting negations in clinical text is crucial for accurate documentation and decision-making.

Large language models for analyzing open text in global health surveys: why children are not accessing vaccine services in the Democratic Republic of the Congo.

International health
BACKGROUND: This study evaluates the use of large language models (LLMs) to analyze free-text responses from large-scale global health surveys, using data from the EnquĂȘte de Couverture Vaccinale (ECV) household coverage surveys from 2020, 2021, 2022...

Radiology report generation using automatic keyword adaptation, frequency-based multi-label classification and text-to-text large language models.

Computers in biology and medicine
BACKGROUND: Radiology reports are essential in medical imaging, providing critical insights for diagnosis, treatment, and patient management by bridging the gap between radiologists and referring physicians. However, the manual generation of radiolog...

From BERT to generative AI - Comparing encoder-only vs. large language models in a cohort of lung cancer patients for named entity recognition in unstructured medical reports.

Computers in biology and medicine
BACKGROUND: Extracting clinical entities from unstructured medical documents is critical for improving clinical decision support and documentation workflows. This study examines the performance of various encoder and decoder models trained for Named ...

Classification of epilepsy seizure types in pediatrics based on Turkish EEG reports.

Epilepsy research
This study focuses on the binary classification of pediatric epilepsy seizure types as focal or generalized using Turkish electroencephalography (EEG) reports, leveraging natural language processing (NLP) and machine learning methodologies. A novel d...

BegoniaGPT: Cultivating the large language model to be an exceptional K-12 English teacher.

Neural networks : the official journal of the International Neural Network Society
Large language models (LLMs) have taken the natural language processing (NLP) domain by storm, and their transformative momentum has surged into the domain of education, giving rise to a nascent wave of education-tailored LLMs. Despite their potentia...

Applications of Natural Language Processing in Otolaryngology: A Scoping Review.

The Laryngoscope
OBJECTIVE: To review the current literature on the applications of natural language processing (NLP) within the field of otolaryngology.

Diagnostic report generation for macular diseases by natural language processing algorithms.

The British journal of ophthalmology
AIMS: To investigate rule-based and deep learning (DL)-based methods for the automatically generating natural language diagnostic reports for macular diseases.

Development of Methods to Assess Readability in Health and Medical Information: A Scoping Review.

Studies in health technology and informatics
This study aimed to extract characteristics of studies involving development of readability measures for health and medical information (HMI) to explore the common themes (strategies) within such developments. Four databases were searched following P...