LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery

LitSense 2.0 (https://www.ncbi.nlm.nih.gov/research/litsense2/) is an advanced biomedical search system enhanced with dense vector semantic retrieval, designed for accessing literature on sentence and paragraph levels. It provides unified access to 38 million PubMed abstracts and 6.6 million full-length articles in the PubMed Central (PMC) Open Access subset, encompassing 1.4 billion sentences and ∼300 million paragraphs, and is updated weekly. Compared to PubMed and PMC, the primary platforms for biomedical information search, LitSense offers cross-platform functionality by searching seamlessly across both PubMed and PMC and returning relevant results at a more granular level. Building on the success of the original LitSense launched in 2018, LitSense 2.0 introduces two major enhancements. The first is the addition of paragraph-level search: users can now choose to search either against sentences or against paragraphs. The second is improved retrieval accuracy via a state-of-the-art biomedical text encoder, ensuring more reliable identification of relevant results across the entire biomedical literature.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-05-16
DOI
https://doi.org/10.1093/nar/gkaf417
Citations
3
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
7.44

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article

LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery

Donald C. Comeau, Shubo Tian, Zhiyong Lu, Won Bae Kim et al.
3 citations
Nucleic Acids Research
Topic Modeling
7.44
article

LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery

Donald C. Comeau, Shubo Tian, Zhiyong Lu, Won Bae Kim, W. John Wilbur, Lana Yeganova
article en
3 citations

Abstract

LitSense 2.0 (https://www.ncbi.nlm.nih.gov/research/litsense2/) is an advanced biomedical search system enhanced with dense vector semantic retrieval, designed for accessing literature on sentence and paragraph levels. It provides unified access to 38 million PubMed abstracts and 6.6 million full-length articles in the PubMed Central (PMC) Open Access subset, encompassing 1.4 billion sentences and ∼300 million paragraphs, and is updated weekly. Compared to PubMed and PMC, the primary platforms for biomedical information search, LitSense offers cross-platform functionality by searching seamlessly across both PubMed and PMC and returning relevant results at a more granular level. Building on the success of the original LitSense launched in 2018, LitSense 2.0 introduces two major enhancements. The first is the addition of paragraph-level search: users can now choose to search either against sentences or against paragraphs. The second is improved retrieval accuracy via a state-of-the-art biomedical text encoder, ensuring more reliable identification of relevant results across the entire biomedical literature.

Nucleic Acids ResearchVol. 53(W1)
National Institutes of Health (US), United States National Library of Medicine (US)
National Institutes of Health
Quality Education
Openalex Percentile: Top 3%
Topic Modeling
7.44
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LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery — Donald C. Comeau, Shubo Tian, et al. · Nucleic Acids Research (2025) | TGRS Research Map | TGRS