ArticleScientific data2019
BioWordVec, improving biomedical word embeddings with subword information and MeSH.
Article in Scientific data, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 149 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
149 citing papers in PubMed.
- Detecting Misspelled Drug Names Using Transformer-Based Language Models: Model Development and External Validation.JMIR medical informatics · 2026Article
- Contrastive learning of adverse events to provide effective and interpretable vector representations for machine-assisted pharmacovigilance.Briefings in bioinformatics · 2026Article
- Benchmarking MeSH-augmented embeddings for biomedical document similarity.Journal of biomedical semantics · 2026Article
- An embedding-based framework enables statistical testing of gene-set function hypotheses inferred by large language models.Nature communications · 2026Article
- Extracting Social Determinants of Health From Electronic Health Records: Development and Comparison of Rule-Based and Large Language Model Methods.JMIR medical informatics · 2026Article
- iS2C2: a cointelligent platform for mechanistic discovery of disease cellular crosstalk.Signal transduction and targeted therapy · 2026Article
- Graph augmented transformers improve chemotherapy toxicity symptom extraction from clinical notes.Nature communications · 2026Article
- Knowledge-based citation reasoning for biomedical domain.Bioinformatics (Oxford, England) · 2026Article
- LLM-Powered Cross-Modal Alignment for Explainable Seizure Detection from EEG.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026Article
- A scalable framework for benchmark embedding models in semantic health-care tasks.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Extracting social determinants of health from electronic health records: development and comparison of rule-based and large language models-based methods.medRxiv : the preprint server for health sciences · 2025Article
- Natural language processing for triage of cerebral large-vessel occlusion.Arquivos de neuro-psiquiatria · 2025Article
- Predicting Acute Cerebrovascular Events in Stroke Alerts Using Large-Language Models and Structured Data.medRxiv : the preprint server for health sciences · 2025Article
- Knowledge based convolutional transformer for joint estimation of PMScientific reports · 2025Article
- Predicting Drug-Side Effect Relationships From Parametric Knowledge Embedded in Biomedical BERT Models: Methodological Study With a Natural Language Processing Approach.JMIR medical informatics · 2025Article
- Benchmarking pre-trained text embedding models in aligning built asset information.Scientific reports · 2025Article
- CSpace: a concept embedding space for biomedical applications.Bioinformatics (Oxford, England) · 2025Article
- Machine learning to predict penumbra core mismatch in acute ischemic stroke using clinical note data.NPJ digital medicine · 2025Article
- Predicting 30-Day Postoperative Mortality and American Society of Anesthesiologists Physical Status Using Retrieval-Augmented Large Language Models: Development and Validation Study.Journal of medical Internet research · 2025Article
- Use of deep learning-based NLP models for full-text data elements extraction for systematic literature review tasks.Scientific reports · 2025Article
89 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Distributed word representations have become an essential foundation for biomedical natural language processing (BioNLP), text mining and information retrieval. Word embeddings are traditionally computed at the word level from a large corpus of unlabeled text, ignoring the information present in the internal structure of words or any information available in domain specific structured resources such as ontologies. However, such information holds potentials for greatly improving the quality of the word representation, as suggested in some recent studies in the general domain. Here we present BioWordVec: an open set of biomedical word vectors/embeddings that combines subword information from unlabeled biomedical text with a widely-used biomedical controlled vocabulary called Medical Subject Headings (MeSH). We assess both the validity and utility of our generated word embeddings over multiple NLP tasks in the biomedical domain. Our benchmarking results demonstrate that our word embeddings can result in significantly improved performance over the previous state of the art in those challenging tasks.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.