Literature DB >> 16778999

Determining prominent subdomains in medicine.

Powell J Bernhardt1, Susanne M Humphrey, Thomas C Rindflesch.   

Abstract

We discuss an automated method for identifying prominent subdomains in medicine. The motivation is to enhance the results of natural language processing by focusing on sublanguages associated with medical specialties concerned with prevalent disorders. At the core of our approach is a statistical system for topical categorization of medical text. A method based on epidemiological evidence is compared to another that considers frequency of occurrence of Medline citations. We suggest the isolation of UMLS terminology peculiar to individual medical specialties as a way of enhancing natural language processing systems in the biomedical domain.

Mesh：

Year:  2005        PMID： 16778999      PMCID： PMC1560510     

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


  13 in total

1.  GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles.

Authors:  C Friedman; P Kra; H Yu; M Krauthammer; A Rzhetsky
Journal:  Bioinformatics       Date:  2001       Impact factor: 6.937

2.  Mapping abbreviations to full forms in biomedical articles.

Authors:  Hong Yu; George Hripcsak; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2002 May-Jun       Impact factor: 4.497

3.  Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program.

Authors:  A R Aronson
Journal:  Proc AMIA Symp       Date:  2001

4.  Evaluating the UMLS as a source of lexical knowledge for medical language processing.

Authors:  C Friedman; H Liu; L Shagina; S Johnson; G Hripcsak
Journal:  Proc AMIA Symp       Date:  2001

5.  A study of abbreviations in MEDLINE abstracts.

Authors:  Hongfang Liu; Alan R Aronson; Carol Friedman
Journal:  Proc AMIA Symp       Date:  2002

6.  The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text.

Authors:  Thomas C Rindflesch; Marcelo Fiszman
Journal:  J Biomed Inform       Date:  2003-12       Impact factor: 6.317

7.  Automated encoding of clinical documents based on natural language processing.

Authors:  Carol Friedman; Lyudmila Shagina; Yves Lussier; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2004-06-07       Impact factor: 4.497

8.  Automatic Indexing of Documents from Journal Descriptors: A Preliminary Investigation.

Authors:  Susanne M Humphrey
Journal:  J Am Soc Inf Sci       Date:  1999

9.  Notations for high efficiency data presentation in mammography.

Authors:  J Starren; S M Johnson
Journal:  Proc AMIA Annu Fall Symp       Date:  1996

10.  Using medical language processing to support real-time evaluation of pneumonia guidelines.

Authors:  M Fiszman; P J Haug
Journal:  Proc AMIA Symp       Date:  2000
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  3 in total

1.  Medical knowledge infused convolutional neural networks for cohort selection in clinical trials.

Authors:  Chi-Jen Chen; Neha Warikoo; Yung-Chun Chang; Jin-Hua Chen; Wen-Lian Hsu
Journal:  J Am Med Inform Assoc       Date:  2019-11-01       Impact factor: 4.497

2.  Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach.

Authors:  Wei-Hung Weng; Kavishwar B Wagholikar; Alexa T McCray; Peter Szolovits; Henry C Chueh
Journal:  BMC Med Inform Decis Mak       Date:  2017-12-01       Impact factor: 2.796

3.  Collecting specialty-related medical terms: Development and evaluation of a resource for Spanish.

Authors:  Pilar López-Úbeda; Alexandra Pomares-Quimbaya; Manuel Carlos Díaz-Galiano; Stefan Schulz
Journal:  BMC Med Inform Decis Mak       Date:  2021-05-04       Impact factor: 2.796
  3 in total

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