Medical WordNet: A New Methodology for the Construction and Validation of Information Resources for Consumer Health

A consumer health information system must be able to comprehend both expert and nonexpert medical vocabulary and to map between the two. We describe an ongoing project to create a new lexical database called Medical WordNet (MWN), consisting of medically relevant terms used by and intelligible to non-expert subjects and supplemented by a corpus of natural-language sentences that is designed to provide medically validated contexts for MWN terms. The corpus derives primarily from online health information sources targeted to consumers, and involves two sub-corpora, called Medical FactNet (MFN) and Medical BeliefNet (MBN), respectively. The former consists of statements accredited as true on the basis of a rigorous process of validation, the latter of statements which non-experts believe to be true. We summarize the MWN / MFN / MBN project, and describe some of its applications.

[1]  Carlo Strapparava,et al.  WordNet for Italian and Its Use for Lexical Deiscrimination , 1997, AI*IA.

[2]  Roberto Basili,et al.  Contextual Word Sense Tuning and Disambiguation , 1997, Appl. Artif. Intell..

[3]  Jason Eisner,et al.  Lexical Semantics , 2020, The Handbook of English Linguistics.

[4]  Olivier Bodenreider,et al.  Characterizing the definitions of anatomical concep ts in WordNet and specialized sources , 2002 .

[5]  Olivier Bodenreider,et al.  Evaluation of WordNet as a source of lay knowledge for molecular biology and genetic diseases: A feasibility study , 2003, MIE.

[6]  Paola Velardi,et al.  Automatic Selection of Class Labels from a Thesaurus for an Effective Semantic Tagging of Corpora , 1997, ANLP.

[7]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[8]  F. Moore Cognitive development and the acquisition of language , 1973 .

[9]  Barry Smith,et al.  On the Application of Formal Principles to Life Science Data: a Case Study in the Gene Ontology , 2004, DILS.

[10]  Barry Smith,et al.  The Role of Foundational Relations in the Alignment of Biomedical Ontologies , 2004, MedInfo.

[11]  Christiane Fellbaum,et al.  Color-X: Using Knowledge From Wordnet for Conceptual Modeling , 1998 .

[12]  Charles J. Fillmore,et al.  The Structure of the Framenet Database , 2003 .

[13]  Alexa T. McCray,et al.  Understanding Search Failures in Consumer Health Information Systems , 2003, AMIA.

[14]  John B. Lowe,et al.  The Berkeley FrameNet Project , 1998, ACL.

[15]  Eneko Agirre,et al.  Exploring Automatic Word Sense Disambiguation with Decision Lists and the Web , 2000, SAIC@COLING.

[16]  Paul Buitelaar,et al.  Ranking and Selecting Synsets by Domain Relevance , 2001 .

[17]  E. Rosch ON THE INTERNAL STRUCTURE OF PERCEPTUAL AND SEMANTIC CATEGORIES1 , 1973 .

[18]  Christiane Fellbaum,et al.  Temporal Indexing Through Lexical Chaining , 1998 .

[19]  Vimla L. Patel,et al.  Patients' and physicians' understanding of health and biomedical concepts: relationship to the design of EMR systems , 2002, J. Biomed. Informatics.

[20]  Olivier Bodenreider,et al.  Investigating subsumption in DL-based terminologies: A Case Study in SNOMED CT , 2004, KR-MED.

[21]  Martha Palmer,et al.  From TreeBank to PropBank , 2002, LREC.

[22]  P. Gorman,et al.  A taxonomy of generic clinical questions: classification study , 2000, BMJ : British Medical Journal.

[23]  Christiane Fellbaum,et al.  On the Semantics of Troponymy , 2002 .

[24]  R. Kazman,et al.  Temporal Indexing Through Lexical Chaining , 1998 .

[25]  Christiane Fellbaum,et al.  English Verbs as a Semantic Net , 1990 .

[26]  Paul Buitelaar,et al.  Extending Synsets with Medical Terms , 2002 .

[27]  Wendy W. Chapman,et al.  In their own words? A terminological analysis of e-mail to a cancer information service , 2002, AMIA.

[28]  Olivier Bodenreider,et al.  Comparing terms, concepts and semantic classes in WordNet and the Unified Medical Language System , 2001 .

[29]  R A Greenes,et al.  Characteristics of Consumer Terminology for Health Information Retrieval , 2002, Methods of Information in Medicine.

[30]  Douglas B. Lenat,et al.  CYC: a large-scale investment in knowledge infrastructure , 1995, CACM.

[31]  Eleanor Rosch,et al.  Principles of Categorization , 1978 .

[32]  Ramanathan V. Guha,et al.  CYC: A Midterm Report , 1990, AI Mag..

[33]  Dagobert Soergel,et al.  Procedures for mapping vocabularies from non-professional discourse a case study: "Consumer medical vocabulary" , 2005, ASIST.

[34]  E. Rosch Cognitive Representations of Semantic Categories. , 1975 .

[35]  P. Newcomer,et al.  Basic Color Terms , 1971, International Journal of American Linguistics.

[36]  James Pustejovsky,et al.  The Generative Lexicon , 1995, CL.

[37]  Maria Lapata The Semantics of Relationships: An Interdisciplinary Perspective , 2003 .

[38]  Pierre Zweigenbaum,et al.  Towards a Medical Question-Answering System: a Feasibility Study , 2003, MIE.

[39]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[40]  Julio Gonzalo,et al.  Indexing with WordNet synsets can improve text retrieval , 1998, WordNet@ACL/COLING.

[41]  M. Ross Quillian,et al.  Retrieval time from semantic memory , 1969 .

[42]  Carlo Strapparava,et al.  Using WordNet to Improve User Modelling in a Web Document Recommender System , 2004 .

[43]  Sanda M. Harabagiu A MARKER PROPAGATION TEXT UNDERSTANDING AND INFERENCE SYSTEM , 1996 .

[44]  Dietmar Rösner,et al.  Finding High-Frequent Synonyms of A Domain-Specific Verb in English Sub-Language of MEDLINE Abstracts Using WordNet , 2004 .

[45]  J. F. M. Burg,et al.  COLOR-X: Using Knowledge from WordNet for Conceptual Modeling , 1996 .

[46]  E. Rosch,et al.  Cognition and Categorization , 1980 .