Literature DB >> 16580973

Status of text-mining techniques applied to biomedical text.

Ramón A-A Erhardt1, Reinhard Schneider, Christian Blaschke.   

Abstract

Scientific progress is increasingly based on knowledge and information. Knowledge is now recognized as the driver of productivity and economic growth, leading to a new focus on the role of information in the decision-making process. Most scientific knowledge is registered in publications and other unstructured representations that make it difficult to use and to integrate the information with other sources (e.g. biological databases). Making a computer understand human language has proven to be a complex achievement, but there are techniques capable of detecting, distinguishing and extracting a limited number of different classes of facts. In the biomedical field, extracting information has specific problems: complex and ever-changing nomenclature (especially genes and proteins) and the limited representation of domain knowledge.

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Year:  2006        PMID: 16580973     DOI: 10.1016/j.drudis.2006.02.011

Source DB:  PubMed          Journal:  Drug Discov Today        ISSN: 1359-6446            Impact factor:   7.851


  25 in total

1.  Automatic extraction of concepts to extend RadLex.

Authors:  Rebecca Hazen; Alex P Van Esbroeck; Pat Mongkolwat; David S Channin
Journal:  J Digit Imaging       Date:  2011-02       Impact factor: 4.056

2.  Automated information extraction of key trial design elements from clinical trial publications.

Authors:  Berry de Bruijn; Simona Carini; Svetlana Kiritchenko; Joel Martin; Ida Sim
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

3.  Extracting causal relations on HIV drug resistance from literature.

Authors:  Quoc-Chinh Bui; Breanndán O Nualláin; Charles A Boucher; Peter M A Sloot
Journal:  BMC Bioinformatics       Date:  2010-02-23       Impact factor: 3.169

Review 4.  A review of analytics and clinical informatics in health care.

Authors:  Allan F Simpao; Luis M Ahumada; Jorge A Gálvez; Mohamed A Rehman
Journal:  J Med Syst       Date:  2014-04-03       Impact factor: 4.460

5.  Building a high-quality sense inventory for improved abbreviation disambiguation.

Authors:  Naoaki Okazaki; Sophia Ananiadou; Jun'ichi Tsujii
Journal:  Bioinformatics       Date:  2010-03-25       Impact factor: 6.937

6.  Automatic vs. manual curation of a multi-source chemical dictionary: the impact on text mining.

Authors:  Kristina M Hettne; Antony J Williams; Erik M van Mulligen; Jos Kleinjans; Valery Tkachenko; Jan A Kors
Journal:  J Cheminform       Date:  2010-03-23       Impact factor: 5.514

7.  Rewriting and suppressing UMLS terms for improved biomedical term identification.

Authors:  Kristina M Hettne; Erik M van Mulligen; Martijn J Schuemie; Bob Ja Schijvenaars; Jan A Kors
Journal:  J Biomed Semantics       Date:  2010-03-31

8.  miRSel: automated extraction of associations between microRNAs and genes from the biomedical literature.

Authors:  Haroon Naeem; Robert Küffner; Gergely Csaba; Ralf Zimmer
Journal:  BMC Bioinformatics       Date:  2010-03-16       Impact factor: 3.169

9.  Arena3D: visualization of biological networks in 3D.

Authors:  Georgios A Pavlopoulos; Seán I O'Donoghue; Venkata P Satagopam; Theodoros G Soldatos; Evangelos Pafilis; Reinhard Schneider
Journal:  BMC Syst Biol       Date:  2008-11-28

10.  Enhancement of chemical entity identification in text using semantic similarity validation.

Authors:  Tiago Grego; Francisco M Couto
Journal:  PLoS One       Date:  2013-05-02       Impact factor: 3.240

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