AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Natural Language Processing

Showing 131 to 140 of 3555 articles

Clear Filters

Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.

Journal of medical Internet research
BACKGROUND: While the COVID-19 pandemic has induced massive discussion of available medications on social media, traditional studies focused only on limited aspects, such as public opinions, and endured reporting biases, inefficiency, and long collec...

Use of natural language processing method to identify regional anesthesia from clinical notes.

Regional anesthesia and pain medicine
INTRODUCTION: Accurate data capture is integral for research and quality improvement efforts. Unfortunately, limited guidance for defining and documenting regional anesthesia has resulted in wide variation in documentation practices, even within indi...

Natural Language Processing and soft data for motor skill assessment: A case study in surgical training simulations.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automated surgical skill assessment using kinematic and video data (hard data) sources has been widely adopted in the literature. However, experts' opinions (soft data) in the form of free-text could be an invaluable source ...

Performance Improvement of a Natural Language Processing Tool for Extracting Patient Narratives Related to Medical States From Japanese Pharmaceutical Care Records by Increasing the Amount of Training Data: Natural Language Processing Analysis and Validation Study.

JMIR medical informatics
BACKGROUND: Patients' oral expressions serve as valuable sources of clinical information to improve pharmacotherapy. Natural language processing (NLP) is a useful approach for analyzing unstructured text data, such as patient narratives. However, few...

Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data.

Journal of translational medicine
BACKGROUND: Single-cell multi-omics technologies, particularly single-cell RNA sequencing (scRNA-seq), have revolutionized our understanding of cellular heterogeneity and development by providing insights into gene expression at the single-cell level...

Vision-language large learning model, GPT4V, accurately classifies the Boston Bowel Preparation Scale score.

BMJ open gastroenterology
INTRODUCTION: Large learning models (LLMs) such as GPT are advanced artificial intelligence (AI) models. Originally developed for natural language processing, they have been adapted for multi-modal tasks with vision-language input. One clinically rel...

Using a Longformer Large Language Model for Segmenting Unstructured Cancer Pathology Reports.

JCO clinical cancer informatics
PURPOSE: Many Natural Language Processing (NLP) methods achieve greater performance when the input text is preprocessed to remove extraneous or unnecessary text. A technique known as text segmentation can facilitate this step by isolating key section...

An NLP-based method to mine gene and function relationships from published articles.

Scientific reports
Understanding the intricacies of genes function within biological systems is paramount for scientific advancement and medical progress. Owing to the evolving landscape of this research and the complexity of biological processes, however, this task pr...

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women.

Experimental biology and medicine (Maywood, N.J.)
Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditional topic modeling, such as Latent Dirichlet Allocation (LDA), faces limitations in capturing the se...