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Biomedical articles share annotations with their citation neighbors

Raul Rodriguez-Esteban
2021 BMC Bioinformatics  
Results With the aid of several large and small annotation databases, this study shows that articles share annotations with their citation neighborhood to the point that the neighborhood's most common  ...  Thus, citations should be considered as a foundation for future knowledge management and annotation of biomedical articles.  ...  articles tend to share annotations with their citation neighbors.  ... 
doi:10.1186/s12859-021-04044-4 pmid:33637047 fatcat:pjzu5vnuvfatvjvn7n5lc274wq

Recommending MeSH terms for annotating biomedical articles

Minlie Huang, Aurélie Névéol, Zhiyong Lu
2011 JAMIA Journal of the American Medical Informatics Association  
Acknowledgments We would like to thank Dr W John Wilbur and Dr Won Kim for providing the L1000 dataset and for retrieving neighbor documents, and thank Dr Alan Aronson and James G Mork for valuable discussions  ...  Our approach shares the same limitations with MTI's Related Citations component 14 and the reflective random indexing approach, 9 as all these approaches rely on neighbor documents' annotations.  ...  CONCLUSION AND FUTURE WORK We presented a ranking-based method to recommend MeSH terms to annotate biomedical articles.  ... 
doi:10.1136/amiajnl-2010-000055 pmid:21613640 pmcid:PMC3168302 fatcat:ym6b6mo4lzemteccrcomutuzne

ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing

Mark Neumann, Daniel King, Iz Beltagy, Waleed Ammar
2019 Proceedings of the 18th BioNLP Workshop and Shared Task  
We detail the performance of two packages of models released in scispaCy and demonstrate their robustness on several tasks and datasets.  ...  This paper describes scis-paCy, a new Python library and models for practical biomedical/scientific text processing, which heavily leverages the spaCy library.  ...  The OntoNotes corpus consists of multiple genres of text, annotated with syntactic and semantic information, but we only use POS and dependency parsing annotations in this work.  ... 
doi:10.18653/v1/w19-5034 dblp:conf/bionlp/NeumannKBA19 fatcat:7yucm2afanbf5m2yccjlzhe7vy

Utilization of Electronic Medical Records and Biomedical Literature to Support Rare Disease Diagnosis (Preprint)

Feichen Shen, Sijia Liu, Yanshan Wang, Andrew Wen, Liwei Wang, Hongfang Liu
2018 JMIR Medical Informatics  
Log likelihood ratio similarity combined with k-nearest neighbor on heterogeneous datasets showed the optimal performance in patient recommendation with area under the precision-recall curve (PRAUC) 0.475  ...  With an exponentially growing volume of electronically accessible medical data, a large volume of information on thousands of rare diseases and their potentially associated diagnostic information is buried  ...  Wang et al made a comparison among clinical notes, biomedical literature, and their combination to test their performances with word embeddings [24] .  ... 
doi:10.2196/11301 pmid:30305261 fatcat:4fz4stf2rveqnf3de2vxftqz24

MeSH Up: effective MeSH text classification for improved document retrieval

Dolf Trieschnigg, Piotr Pezik, Vivian Lee, Franciska de Jong, Wessel Kraaij, Dietrich Rebholz-Schuhmann
2009 Computer applications in the biosciences : CABIOS  
A K-Nearest Neighbor system clearly outperforms the other published approaches and scales well with large amounts of text using the full MeSH thesaurus.  ...  Conclusions: The annotation of biomedical texts using controlled vocabularies such as MeSH can be automated to improve text-only IR.  ...  One drawback is that it may return MeSH terms which only share a single word with the text to classify.  ... 
doi:10.1093/bioinformatics/btp249 pmid:19376821 pmcid:PMC2682526 fatcat:yo4hava6ozhupfny7jrt5oeylq

DeepMeSH: deep semantic representation for improving large-scale MeSH indexing

Shengwen Peng, Ronghui You, Hongning Wang, Chengxiang Zhai, Hiroshi Mamitsuka, Shanfeng Zhu
2016 Bioinformatics  
Motivation: Medical Subject Headings (MeSH) indexing, which is to assign a set of MeSH main headings to citations, is crucial for many important tasks in biomedical text mining and information retrieval  ...  Results: DeepMeSH achieved a Micro F-measure of 0.6323, 2% higher than 0.6218 of MeSHLabeler and 12% higher than 0.5637 of MTI, for BioASQ3 challenge data with 6000 citations.  ...  Then, these neighbor citations and their similarities are used to score the candidate MHs.  ... 
doi:10.1093/bioinformatics/btw294 pmid:27307646 pmcid:PMC4908368 fatcat:ne5k5aahvnd4lkecnrohw2vnpy

Biomedical semantic indexing by deep neural network with multi-task learning

Yongping Du, Yunpeng Pan, Chencheng Wang, Junzhong Ji
2018 BMC Bioinformatics  
Biomedical semantic indexing is important for information retrieval and many other research fields in bioinformatics. It annotates biomedical citations with Medical Subject Headings.  ...  The auxiliary task is a regression task that predicts the MeSH number of the citation and provides hints for the network to make it converge faster.  ...  About this supplement This article has been published as part of BMC Bioinformatics Volume 19 Supplement 20, 2018: Selected articles from the IEEE BIBM International Conference on Bioinformatics & Biomedicine  ... 
doi:10.1186/s12859-018-2534-2 fatcat:njnof4vpzjbihkhuu36rjf2m4y

Improved Biomedical Word Embeddings in the Transformer Era [article]

Jiho Noh, Ramakanth Kavuluru
2020 arXiv   pre-print
(MeSH) concepts in biomedical citations.  ...  Biomedical word embeddings are usually pre-trained on free text corpora with neural methods that capture local and global distributional properties.  ...  It has over 30 million PubMed citations (abstracts and titles from the 2020 baseline) and over 3 million full-text articles with high-quality annotations for genes (and their variants), diseases, chemicals  ... 
arXiv:2012.11808v2 fatcat:bis5kguhnjcsfodwhac5hgzms4

A Meta-analysis of Semantic Classification of Citations

Suchetha N. Kunnath, Drahomira Herrmannova, David Pride, Petr Knoth
2021 Quantitative Science Studies  
In particular, we investigate the approaches for characterising citations based on their semantic type.  ...  We conduct this literature review as a metaanalysis covering 60 scholarly articles in this domain.  ...  better than (4)Positive -0.1% Biomedical articles fine-grained citation (5)Practical -1% (PubMed) function classification  ... 
doi:10.1162/qss_a_00159 fatcat:ng6ogcs3rzbr5c5jyulax5cddy

Scientific document summarization via citation contextualization and scientific discourse

Arman Cohan, Nazli Goharian
2017 International Journal on Digital Libraries  
We finally propose a method for summarizing scientific papers by leveraging the faceted citations and their corresponding contexts.  ...  We evaluate our proposed method on two scientific summarization datasets in the biomedical and computational linguistics domains.  ...  One way to address such problems is to consider the citations in their context from the reference article.  ... 
doi:10.1007/s00799-017-0216-8 fatcat:4zwdaqixnzei3i6yegahz3gxge

Linking genes to literature: text mining, information extraction, and retrieval applications for biology

Martin Krallinger, Alfonso Valencia, Lynette Hirschman
2008 Genome Biology  
The current trend in biomedical text mining points toward an increasing diversification in terms of application types and techniques, together with integration of domain-specific resources such as ontologies  ...  The aim of the BioCreative challenge is to promote the development of such tools and to provide insight into their performance.  ...  This article has been published as part of Genome Biology Volume 9 Supplement 2, 2008: The BioCreative II -Critical Assessment for Information Extraction in Biology Challenge.  ... 
doi:10.1186/gb-2008-9-s2-s8 pmid:18834499 pmcid:PMC2559992 fatcat:oeqr7ctzgjeo5nnw53fimelwxa

Frontiers of biomedical text mining: current progress

P. Zweigenbaum, D. Demner-Fushman, H. Yu, K. B. Cohen
2007 Briefings in Bioinformatics  
In this article we review the current state of the art in biomedical text mining or 'BioNLP' in general, focusing primarily on papers published within the past year.  ...  However, a number of problems at the frontiers of biomedical text mining continue to present interesting challenges and opportunities for great improvements and interesting research.  ...  We wish to thank the journal's anonymous reviewers, whose insightful comments helped significantly improve this article.  ... 
doi:10.1093/bib/bbm045 pmid:17977867 pmcid:PMC2516302 fatcat:4nfbokb7lfdjbnkijw2v6754qy

Literature based discovery of gene clusters using phylogenetic methods

Indra Neil Sarkar, Abha Agrawal
2006 AMIA Annual Symposium Proceedings  
In this study, we demonstrate the utility of existing phylogenetic methods for organizing 375 genes associated with Breast Cancer using the MeSH annotations from over 35,000 Medline articles.  ...  Biomedical literature can offer valuable information for organizing genes associated with the etiology and pathogenesis of disease.  ...  ACKNOWLEDGMENTS The authors are grateful for the insightful discussions with Drs.  ... 
pmid:17238429 pmcid:PMC1839645 fatcat:u6wkz4i4yrerrnkryhmyuz2u5y

Implementing Recommendation Algorithms in a Large-Scale Biomedical Science Knowledge Base [article]

Jessica Perrie and Yanqi Hao and Zack Hayat and Recep Colak and Kelly Lyons and Shankar Vembu and Sam Molyneux
2017 arXiv   pre-print
The number of biomedical research articles published has doubled in the past 20 years.  ...  We implemented several recommendation algorithms and evaluated their efficiency in this large-scale biomedical knowledge base.  ...  Acknowledgements The authors would like to thank Meta's Data Science team for their valuable feedback and support during this work.  ... 
arXiv:1710.08579v1 fatcat:niur7ahvpjd7xd54nurdaig3dy

Identifying clinical terms in free-text notes using ontology-guided machine learning (Preprint)

Aryan Arbabi, David R Adams, Sanja Fidler, Michael Brudno
2018 JMIR Medical Informatics  
In addition, most machine learning methods typically require large corpora of annotated text that cover all classes of concepts, which can be extremely difficult to obtain for biomedical ontologies.  ...  We tested our model trained on HPO by using two different data sets: 288 annotated PubMed abstracts and 39 clinical reports.  ...  We evaluated the accuracy of our model trained on the HPO on two different data sets: • PubMed: This data set contains 228 PubMed article abstracts, gathered and manually annotated with HPO concepts by  ... 
doi:10.2196/12596 pmid:31094361 pmcid:PMC6533869 fatcat:r2zenmdtyfft5bh367t5bkzizu
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