LitSense 2.0:人工智能生物医学信息检索,具有句子和段落级别的知识发现。

IF 16.6 2区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Lana Yeganova,Won Kim,Shubo Tian,Donald C Comeau,W John Wilbur,Zhiyong Lu
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引用次数: 0

摘要

LitSense 2.0 (https://www.ncbi.nlm.nih.gov/research/litsense2/)是一个先进的生物医学搜索系统,增强了密集向量语义检索,旨在访问句子和段落级别的文献。它提供了对PubMed Central (PMC)开放获取子集中的3800万篇PubMed摘要和660万篇全文文章的统一访问,包括14亿个句子和约3亿个段落,并且每周更新一次。与PubMed和PMC(生物医学信息搜索的主要平台)相比,LitSense提供了跨平台功能,可以在PubMed和PMC之间无缝搜索,并在更细粒度的级别返回相关结果。在2018年推出的原始LitSense成功的基础上,LitSense 2.0引入了两个主要增强功能。首先是增加了段落级搜索:用户现在可以选择根据句子或段落进行搜索。第二是通过最先进的生物医学文本编码器提高检索精度,确保在整个生物医学文献中更可靠地识别相关结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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来源期刊
Nucleic Acids Research
Nucleic Acids Research 生物-生化与分子生物学
CiteScore
27.10
自引率
4.70%
发文量
1057
审稿时长
2 months
期刊介绍: Nucleic Acids Research (NAR) is a scientific journal that publishes research on various aspects of nucleic acids and proteins involved in nucleic acid metabolism and interactions. It covers areas such as chemistry and synthetic biology, computational biology, gene regulation, chromatin and epigenetics, genome integrity, repair and replication, genomics, molecular biology, nucleic acid enzymes, RNA, and structural biology. The journal also includes a Survey and Summary section for brief reviews. Additionally, each year, the first issue is dedicated to biological databases, and an issue in July focuses on web-based software resources for the biological community. Nucleic Acids Research is indexed by several services including Abstracts on Hygiene and Communicable Diseases, Animal Breeding Abstracts, Agricultural Engineering Abstracts, Agbiotech News and Information, BIOSIS Previews, CAB Abstracts, and EMBASE.
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