ArticleNucleic acids research2019
LitSense: making sense of biomedical literature at sentence level.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 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
35 citing papers in PubMed.
- An embedding-based framework enables statistical testing of gene-set function hypotheses inferred by large language models.Nature communications · 2026Article
- A unified knowledge graph linking foodomics to chemical-disease networks and flavor profiles.NPJ science of food · 2026Article
- VectorSage: enhancing PubMed article retrieval with advanced semantic search.Bioinformatics advances · 2026Article
- Using Individual Service Funds (ISFs) to Improve Access to Self-Directed Support for Adults With Intellectual Disabilities: A Participatory Realist Review.Journal of applied research in intellectual disabilities : JARID · 2025Review
- Transcriptomic-Driven Drug Repurposing Reveals SP600125 as a Promising Drug Candidate for the Treatment of Glial-Mesenchymal Transition in Glioblastoma.International journal of molecular sciences · 2025Article
- LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery.Nucleic acids research · 2025Article
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- Benchmarking large language models for biomedical natural language processing applications and recommendations.Nature communications · 2025Article
- Inferring Drug-Gene Relationships in Cancer Using Literature-Augmented Large Language Models.Cancer research communications · 2025Article
- Lit-OTAR framework for extracting biological evidences from literature.Bioinformatics (Oxford, England) · 2025Article
- Taught by a Robot: A Trainee Perspective on Artificial Intelligence in Medical School Education.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2025Article
- Gut microbiome-mediated epigenetic modifications in gastric cancer: a comprehensive multiomics analysis.Frontiers in cellular and infection microbiology · 2025Article
- The Multienzyme Complex Nature of Dehydroepiandrosterone Sulfate Biosynthesis.International journal of molecular sciences · 2024Article
- PubMed and beyond: biomedical literature search in the age of artificial intelligence.EBioMedicine · 2024Review
- MedCPT: Contrastive Pre-trained Transformers with large-scale PubMed search logs for zero-shot biomedical information retrieval.Bioinformatics (Oxford, England) · 2023Article
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- Uncharacterized Proteins CxORFx: Subinteractome Analysis and Prognostic Significance in Cancers.International journal of molecular sciences · 2023Article
- OpCitance: Citation contexts identified from the PubMed Central open access articles.Scientific data · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Literature search is a routine practice for scientific studies as new discoveries build on knowledge from the past. Current tools (e.g. PubMed, PubMed Central), however, generally require significant effort in query formulation and optimization (especially in searching the full-length articles) and do not allow direct retrieval of specific statements, which is key for tasks such as comparing/validating new findings with previous knowledge and performing evidence attribution in biocuration. Thus, we introduce LitSense, which is the first web-based system that specializes in sentence retrieval for biomedical literature. LitSense provides unified access to PubMed and PMC content with over a half-billion sentences in total. Given a query, LitSense returns best-matching sentences using both a traditional term-weighting approach that up-weights sentences that contain more of the rare terms in the user query as well as a novel neural embedding approach that enables the retrieval of semantically relevant results without explicit keyword match. LitSense provides a user-friendly interface that assists its users to quickly browse the returned sentences in context and/or further filter search results by section or publication date. LitSense also employs PubTator to highlight biomedical entities (e.g. gene/proteins) in the sentences for better result visualization. LitSense is freely available at https://www.ncbi.nlm.nih.gov/research/litsense.
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.