AIMC Topic: PubMed

Clear Filters Showing 131 to 140 of 157 articles

Using sentiment analysis to identify similarities and differences in research topics and medical subject headings (MeSH terms) between Medicine (Baltimore) and the Journal of the Formosan Medical Association (JFMA) in 2020: A bibliometric study.

Medicine
BACKGROUND:: Little systematic information has been collected about the nature and types of articles published in 2 journals by identifying the latent topics and analyzing the extracted research themes and sentiments using text mining and machine lea...

Gender-sensitive word embeddings for healthcare.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To analyze gender bias in clinical trials, to design an algorithm that mitigates the effects of biases of gender representation on natural-language (NLP) systems trained on text drawn from clinical trials, and to evaluate its performance.

BioBERT and Similar Approaches for Relation Extraction.

Methods in molecular biology (Clifton, N.J.)
In biomedicine, facts about relations between entities (disease, gene, drug, etc.) are hidden in the large trove of 30 million scientific publications. The curated information is proven to play an important role in various applications such as drug r...

Text Mining and Machine Learning Protocol for Extracting Human-Related Protein Phosphorylation Information from PubMed.

Methods in molecular biology (Clifton, N.J.)
In the modern health care research, protein phosphorylation has gained an enormous attention from the researchers across the globe and requires automated approaches to process a huge volume of data on proteins and their modifications at the cellular ...

Artificial intelligence behind the scenes: PubMed's Best Match algorithm.

Journal of the Medical Library Association : JMLA
This article focuses on PubMed's Best Match sorting algorithm, presenting a simplified explanation of how it operates and highlighting how artificial intelligence affects search results in ways that are not seen by users. We further discuss user sear...

The Classification of Short Scientific Texts Using Pretrained BERT Model.

Studies in health technology and informatics
Automated text classification is a natural language processing (NLP) technology that could significantly facilitate scientific literature selection. A specific topical dataset of 630 article abstracts was obtained from the PubMed database. We propose...

Text mining for modeling of protein complexes enhanced by machine learning.

Bioinformatics (Oxford, England)
MOTIVATION: Procedures for structural modeling of protein-protein complexes (protein docking) produce a number of models which need to be further analyzed and scored. Scoring can be based on independently determined constraints on the structure of th...

Large-scale entity representation learning for biomedical relationship extraction.

Bioinformatics (Oxford, England)
MOTIVATION: The automatic extraction of published relationships between molecular entities has important applications in many biomedical fields, ranging from Systems Biology to Personalized Medicine. Existing works focused on extracting relationships...

Health informatics publication trends in Saudi Arabia: a bibliometric analysis over the last twenty-four years.

Journal of the Medical Library Association : JMLA
OBJECTIVE: Understanding health informatics (HI) publication trends in Saudi Arabia may serve as a framework for future research efforts and contribute toward meeting national "e-Health" goals. The authors' intention was to understand the state of th...

Biomedical named entity recognition and linking datasets: survey and our recent development.

Briefings in bioinformatics
Natural language processing (NLP) is widely applied in biological domains to retrieve information from publications. Systems to address numerous applications exist, such as biomedical named entity recognition (BNER), named entity normalization (NEN) ...