Meshable: searching PubMed abstracts by utilizing MeSH and MeSH-derived topical terms

نویسندگان

  • Sun Kim
  • Lana Yeganova
  • W. John Wilbur
چکیده

UNLABELLED Medical Subject Headings (MeSH(®)) is a controlled vocabulary for indexing and searching biomedical literature. MeSH terms and subheadings are organized in a hierarchical structure and are used to indicate the topics of an article. Biologists can use either MeSH terms as queries or the MeSH interface provided in PubMed(®) for searching PubMed abstracts. However, these are rarely used, and there is no convenient way to link standardized MeSH terms to user queries. Here, we introduce a web interface which allows users to enter queries to find MeSH terms closely related to the queries. Our method relies on co-occurrence of text words and MeSH terms to find keywords that are related to each MeSH term. A query is then matched with the keywords for MeSH terms, and candidate MeSH terms are ranked based on their relatedness to the query. The experimental results show that our method achieves the best performance among several term extraction approaches in terms of topic coherence. Moreover, the interface can be effectively used to find full names of abbreviations and to disambiguate user queries. AVAILABILITY AND IMPLEMENTATION https://www.ncbi.nlm.nih.gov/IRET/MESHABLE/ CONTACT: [email protected] SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

OvidSP Medline-to-PubMed search filter translation: a methodology for extending search filter range to include PubMed's unique content

BACKGROUND PubMed translations of OvidSP Medline search filters offer searchers improved ease of access. They may also facilitate access to PubMed's unique content, including citations for the most recently published biomedical evidence. Retrieving this content requires a search strategy comprising natural language terms ('textwords'), rather than Medical Subject Headings (MeSH). We describe a ...

متن کامل

Distributed Representations for Automating MeSH Indexing

7 Manual MeSH indexing of the millions of journal articles cataloged in 8 PubMed each year has become a daunting and expensive challenge for the 9 National Library of Medicine. While the prospect of automated indexing is 10 tempting, the requisite task of multilabel hierarchical classification is a 11 difficult one. This article explores the possibility of generating distributed 12 vector repre...

متن کامل

Volume Decomposition and Feature Recognition for Hexahedral Mesh Generation

Considerable progress has been made on automatic hexahedral mesh generation in recent years. Several automatic meshing algorithms have proven to be very reliable on certain classes of geometry. While it is always worth pursuing general algorithms viable on more general geometry, a combination of the well-established algorithms is ready to take on classes of complicated geometry. By partitioning...

متن کامل

Text-Based Medical Case Retrieval Using MeSH Ontology

Our approach to the ImageCLEF medical case retrieval task consists of text-only retrieval combined with utilizing the Medical Subject Headings (MeSH) ontology. MeSH terms extracted from the query are used for query expansion or query term weighting. MeSH annotations of documents available from PubMed Central are added to the corpus. Retrieval results improve slightly upon full-text retrieval.

متن کامل

Emerging Trend Prediction in Biomedical Literature

We present a study on how to predict new emerging trends in the biomedical domain based on textual data. We thereby propose a way of anticipating the transformation of arbitrary information into ground thruth knowledge by predicting the inclusion of new terms into the MeSH ontology. We also discuss the preparation of a dataset for the evaluation of emerging trend prediction algorithms that is b...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 32  شماره 

صفحات  -

تاریخ انتشار 2016