Literature DB >> 21347046

The Lexicon Builder Web service: Building Custom Lexicons from two hundred Biomedical Ontologies.

Gautam K Parai1, Clement Jonquet, Rong Xu, Mark A Musen, Nigam H Shah.   

Abstract

Domain specific biomedical lexicons are extensively used by researchers for natural language processing tasks. Currently these lexicons are created manually by expert curators and there is a pressing need for automated methods to compile such lexicons. The Lexicon Builder Web service addresses this need and reduces the investment of time and effort involved in lexicon maintenance. The service has three components: Inclusion - selects one or several ontologies (or its branches) and includes preferred names and synonym terms; Exclusion - filters terms based on the term's Medline frequency, syntactic type, UMLS semantic type and match with stopwords; Output - aggregates information, handles compression and output formats. Evaluation demonstrates that the service has high accuracy and runtime performance. It is currently being evaluated for several use cases to establish its utility in biomedical information processing tasks. The Lexicon Builder promotes collaboration, sharing and standardization of lexicons amongst researchers by automating the creation, maintainence and cross referencing of custom lexicons.

Mesh:

Year:  2010        PMID: 21347046      PMCID: PMC3041331     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  16 in total

1.  Creating mappings for ontologies in biomedicine: simple methods work.

Authors:  Amir Ghazvinian; Natalya F Noy; Mark A Musen
Journal:  AMIA Annu Symp Proc       Date:  2009-11-14

Review 2.  Text mining and ontologies in biomedicine: making sense of raw text.

Authors:  Irena Spasic; Sophia Ananiadou; John McNaught; Anand Kumar
Journal:  Brief Bioinform       Date:  2005-09       Impact factor: 11.622

Review 3.  A survey of current work in biomedical text mining.

Authors:  Aaron M Cohen; William R Hersh
Journal:  Brief Bioinform       Date:  2005-03       Impact factor: 11.622

4.  Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics.

Authors:  Hui Cao; Marianthi Markatou; Genevieve B Melton; Michael F Chiang; George Hripcsak
Journal:  AMIA Annu Symp Proc       Date:  2005

5.  Extracting structured medication event information from discharge summaries.

Authors:  Sigfried Gold; Noémie Elhadad; Xinxin Zhu; James J Cimino; George Hripcsak
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

6.  Integrating text mining into the MGI biocuration workflow.

Authors:  K G Dowell; M S McAndrews-Hill; D P Hill; H J Drabkin; J A Blake
Journal:  Database (Oxford)       Date:  2009-11-21       Impact factor: 3.451

7.  Building a biomedical ontology recommender web service.

Authors:  Clement Jonquet; Mark A Musen; Nigam H Shah
Journal:  J Biomed Semantics       Date:  2010-06-22

8.  The open biomedical annotator.

Authors:  Clement Jonquet; Nigam H Shah; Mark A Musen
Journal:  Summit Transl Bioinform       Date:  2009-03-01

9.  BioPortal: ontologies and integrated data resources at the click of a mouse.

Authors:  Natalya F Noy; Nigam H Shah; Patricia L Whetzel; Benjamin Dai; Michael Dorf; Nicholas Griffith; Clement Jonquet; Daniel L Rubin; Margaret-Anne Storey; Christopher G Chute; Mark A Musen
Journal:  Nucleic Acids Res       Date:  2009-05-29       Impact factor: 16.971

10.  Text mining for biology--the way forward: opinions from leading scientists.

Authors:  Russ B Altman; Casey M Bergman; Judith Blake; Christian Blaschke; Aaron Cohen; Frank Gannon; Les Grivell; Udo Hahn; William Hersh; Lynette Hirschman; Lars Juhl Jensen; Martin Krallinger; Barend Mons; Seán I O'Donoghue; Manuel C Peitsch; Dietrich Rebholz-Schuhmann; Hagit Shatkay; Alfonso Valencia
Journal:  Genome Biol       Date:  2008-09-01       Impact factor: 13.583

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  10 in total

1.  The National Center for Biomedical Ontology.

Authors:  Mark A Musen; Natalya F Noy; Nigam H Shah; Patricia L Whetzel; Christopher G Chute; Margaret-Anne Story; Barry Smith
Journal:  J Am Med Inform Assoc       Date:  2011-11-10       Impact factor: 4.497

2.  Mining the pharmacogenomics literature--a survey of the state of the art.

Authors:  Udo Hahn; K Bretonnel Cohen; Yael Garten; Nigam H Shah
Journal:  Brief Bioinform       Date:  2012-07       Impact factor: 11.622

3.  Identifying phenotypic signatures of neuropsychiatric disorders from electronic medical records.

Authors:  Svetlana Lyalina; Bethany Percha; Paea LePendu; Srinivasan V Iyer; Russ B Altman; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2013-08-16       Impact factor: 4.497

4.  Unified Medical Language System term occurrences in clinical notes: a large-scale corpus analysis.

Authors:  Stephen T Wu; Hongfang Liu; Dingcheng Li; Cui Tao; Mark A Musen; Christopher G Chute; Nigam H Shah
Journal:  J Am Med Inform Assoc       Date:  2012-04-04       Impact factor: 4.497

5.  Building the graph of medicine from millions of clinical narratives.

Authors:  Samuel G Finlayson; Paea LePendu; Nigam H Shah
Journal:  Sci Data       Date:  2014-09-16       Impact factor: 6.444

6.  Predicting Future Cardiovascular Events in Patients With Peripheral Artery Disease Using Electronic Health Record Data.

Authors:  Elsie Gyang Ross; Kenneth Jung; Joel T Dudley; Li Li; Nicholas J Leeper; Nigam H Shah
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2019-03

7.  Practice-based evidence: profiling the safety of cilostazol by text-mining of clinical notes.

Authors:  Nicholas J Leeper; Anna Bauer-Mehren; Srinivasan V Iyer; Paea Lependu; Cliff Olson; Nigam H Shah
Journal:  PLoS One       Date:  2013-05-23       Impact factor: 3.240

8.  Network analysis of unstructured EHR data for clinical research.

Authors:  Anna Bauer-Mehren; Paea Lependu; Srinivasan V Iyer; Rave Harpaz; Nicholas J Leeper; Nigam H Shah
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2013-03-18

9.  Profiling risk factors for chronic uveitis in juvenile idiopathic arthritis: a new model for EHR-based research.

Authors:  Tyler S Cole; Jennifer Frankovich; Srinivasan Iyer; Paea Lependu; Anna Bauer-Mehren; Nigam H Shah
Journal:  Pediatr Rheumatol Online J       Date:  2013-12-03       Impact factor: 3.054

10.  Statin Intensity or Achieved LDL? Practice-based Evidence for the Evaluation of New Cholesterol Treatment Guidelines.

Authors:  Elsie Gyang Ross; Nigam Shah; Nicholas Leeper
Journal:  PLoS One       Date:  2016-05-26       Impact factor: 3.240

  10 in total

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