The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text
Tài liệu tham khảo
Haynes, 1994, Developing optimal search strategies for detecting clinically sound studies in MEDLINE, J. Am. Med. Inform. Assoc., 1, 447, 10.1136/jamia.1994.95153434
Mendonca EA, Johnson SB, Seol YH, Cimino JJ. Analyzing the semantics of patient data to rank records of literature retrieval. In: Proceedings of the Workshop on Natural Language Processing in the Biomedical Domain of the Association of Computational Linguistics; 2002. p. 69–75
Craven, 1999, Constructing biological knowledge bases by extracting information from text sources, Proc. Int. Conf. Intell. Syst. Mol. Biol., 77
Rosario B, Hearst M. Classifying the semantic relations in noun compounds via a domain-specific lexical hierarchy. In: Proceedings of Conference on Empirical Methods in Natural Language Processing; June 2001. p. 82–90
Hripcsak, 1995, Unlocking clinical data from narrative reports: a study of natural language processing, Ann. Intern. Med., 122, 681, 10.7326/0003-4819-122-9-199505010-00007
Fiszman, 2000, Automatic detection of acute bacterial pneumonia from chest X-ray reports, J. Am. Med. Inform. Assoc., 7, 593, 10.1136/jamia.2000.0070593
Grishman, 2002, Information extraction for enhanced access to disease outbreak reports, J. Biomed. Inform., 35, 236, 10.1016/S1532-0464(03)00013-3
Hahn, 2002, MEDSYNDIKATE—a natural language system for the extraction of medical information from findings reports, Int. J. Med. Inf., 67, 63, 10.1016/S1386-5056(02)00053-9
Friedman, 2001, GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles, Bioinformatics, 17, S74, 10.1093/bioinformatics/17.suppl_1.S74
Rosario B, Hearst M, Fillmore C. The descent of hierarchy, and selection in relational semantics. In: Proceedings of the Workshop on Natural Language Processing in the Biomedical Domain, Association for Computational Linguistics; 2002. p. 247–54
Spyns, 1996, Natural language processing in medicine: an overview, Methods Inf. Med., 35, 285
Friedman, 1999, Natural language processing and its future in medicine, Acad. Med., 74, 890, 10.1097/00001888-199908000-00012
Rindflesch, 2000, Argument identification for arterial branching predications asserted in cardiac catheterization reports, Proc. AMIA Symp., 704
Rindflesch, 2000, EDGAR: extraction of drugs, genes and relations from the biomedical literature, Pac. Symp. Biocomput., 517
Rindflesch TC, Rajan J, Hunter L. Extracting molecular binding relationships from biomedical text. In: Proceedings of the Sixth Applied Natural Language Processing Conference, Association for Computational Linguistics; 2000. p. 188–95
Srinivasan, 2002, Exploring text mining from MEDLINE, Proc. AMIA Symp., 722
Baud, 1998, Alternative ways for knowledge collection, indexing and robust language retrieval, Methods Inf. Med., 37, 315
Humphreys, 1998, The unified medical language system: an informatics research collaboration, J. Am. Med. Inform. Assoc., 5, 1, 10.1136/jamia.1998.0050001
Amaral, 2000, NLP techniques associated with the OpenGALEN ontology for semi-automatic textual extraction of medical knowledge: abstracting and mapping equivalent linguistic and logistic constructs, Proc. AMIA Symp., 76
Friedman, 1994, A general natural-language text processor for clinical radiology, J. Am. Med. Inform. Assoc., 1, 161, 10.1136/jamia.1994.95236146
Friedman, 2000, A broad-coverage natural language processing system, Proc. AMIA Symp., 270
Sager, 1994, Natural language processing and the representation of clinical data, J. Am. Med. Inform. Assoc., 1, 142, 10.1136/jamia.1994.95236145
Friedman, 2001, Evaluating the UMLS as a source of lexical knowledge for medical language processing, Proc. AMIA Symp., 189
Knirsch, 1998, Respiratory isolation of tuberculosis patients using clinical guidelines and an automated clinical decision support system, Infect Control Hosp. Epidemiol., 19, 94, 10.2307/30141996
Elkins, 2000, Coding neuroradiology reports for the Northern Manhattan Stroke Study: a comparison of natural language processing and manual review, Comput. Biomed. Res., 33, 1, 10.1006/cbmr.1999.1535
Johnson, 1993, Interpreting natural language queries using the UMLS, Proc. Annu. Symp. Comput. Appl. Med. Care, 294
Rassinoux, 1995, Analysis of medical texts based on a sound medical model, Proc. Annu. Symp. Comput. Appl. Med. Care, 27
Rector, 1994, The GALEN project, Comput. Methods Programs Biomed., 45, 75, 10.1016/0169-2607(94)90020-5
Haug, 1994, A natural language understanding system combining syntactic and semantic techniques, Proc. Annu. Symp. Comput. Appl. Med. Care, 247
Fiszman, 2000, Using medical language processing to support real-time evaluation of pneumonia guidelines, Proc. AMIA Symp., 235
Gundersen, 1996, Development and evaluation of a computerized admission diagnoses encoding system, Comput. Biomed. Res., 29, 351, 10.1006/cbmr.1996.0026
Christensen L, Haug PJ, Fiszman M. MPLUS: a probabilistic medical language understanding system. In: Proceedings of the Workshop on Natural Language Processing in the Biomedical Domain, Association for Computational Linguistics; 2002. p. 29–36
Zweigenbaum, 1995, A multi-lingual architecture for building a normalised conceptual representation from medical language, Proc. Annu. Symp. Comput. Appl. Med. Care, 357
Zweigenbaum, 1997, Evaluating a normalized conceptual representation produced from natural language patient discharge summaries, Proc. AMIA Annu. Fall Symp., 590
Hahn, 1999, How knowledge drives understanding—matching medical ontologies with the needs of medical language processing, Artif. Intell. Med., 15, 25, 10.1016/S0933-3657(98)00044-X
Hahn, 2000, MEDSYNDIKATE—design considerations for an ontology-based medical text understanding system, Proc. AMIA Symp., 330
Romacker, 1999, Streamlining semantic interpretation for medical narratives, Proc. AMIA Symp., 925
Hearst, MA. Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the Fourteenth International Conference on Computational Linguistics (COLING); 1992. p. 539–45
Brachman, 1983, 1983. What IS-A is and isn’t: an analysis of taxonomic links in semantic networks, Computer, 16, 30, 10.1109/MC.1983.1654194
Burgun A, Bodenreider O. Aspects of the taxonomic relation in the biomedical domain. In: Collected papers from the Second International Conference “Formal Ontology in Information System”; 2001 p. 222–33
Bodenreider O, Burgun A, Rindflesch TC. Lexically suggested hyponymic relations among medical terms and their representation in the UMLS. In: Proceedings of the Conference on Terminology and Artificial Intelligence; 2001. p. 11–21
Hahn, 1999, Discourse structures in medical reports—watch out! The generation of referentially coherent and valid text knowledge bases in the MEDSYNDIKATE system, Int. J. Med. Inf., 53, 1, 10.1016/S1386-5056(98)00091-4
Chafe, 1975, Givenness, contrastiveness, definiteness, subjects, topics, and point of view, 25
Bodenreider O, Burgun A. Characterizing the definitions of anatomical concepts in WordNet and specialized sources. In: Proceedings of the First Global WordNet Conference; 2002. p. 223–30
McCray, 1994, Lexical methods for managing variation in biomedical terminologies, Proc. Annu. Symp. Comput. Appl. Med. Care, 235
McCray AT. Representing biomedical knowledge in the UMLS Semantic Network. High-performance medical libraries: advances in information management for the virtual era. Meckler Publishing; 1993. p. 45–55
McCray, 2001, Aggregating UMLS semantic types for reducing conceptual complexity, Medinfo, 10, 216
Chen, 2002, Partitioning the UMLS semantic network, IEEE Trans. Inf. Technol. Biomed., 6, 102, 10.1109/TITB.2002.1006296
Perl, 2002, The cohesive metaschema: a higher-level abstraction of the UMLS Semantic Network, J. Biomed. Inform., 35, 194, 10.1016/S1532-0464(02)00528-2
Zhang, 2002, Enriching the Structure of the UMLS Semantic Network, Proc. AMIA Symp., 939
Cutting D, Kupiec J, Pedersen J, Sibun P. A practical part-of-speech tagger. In: Proceedings of the Third Conference on Applied Natural Language Processing; 1992. p. 133–40
Aronson, 2001, Effective mapping of biomedical text to the UMLS Metathesaurus: The MetaMap program, Proc. AMIA Symp., 17
Aronson, 2000, The NLM indexing initiative, Proc. AMIA Symp., 17
Rindflesch TC. Integrating natural language processing and biomedical domain knowledge for increased information retrieval effectiveness. in: Proceedings of the Fifth Annual Dual-use Technologies and Applications Conference; 1995. p. 260–5
Gildea D, Palmer M. The necessity of parsing for predicate argument recognition. In: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistic; 2002. p. 146–239
Liu, 2002, A study of abbreviations in MEDLINE abstracts, Proc. AMIA Symp., 464
Wren, 2002, Heuristics for identification of acronym-definition patterns within text: towards an automated construction of comprehensive acronym-definition dictionaries, Methods Inf. Med., 41, 426, 10.1055/s-0038-1634373
Yu, 2002, Mapping abbreviations to full forms in electronic articles, J. Am. Med. Inform. Assoc., 9, 262, 10.1197/jamia.M0913
Hripcsak, 1999, A reliability study for evaluating information extraction from radiology reports, J. Am. Med. Inform. Assoc., 6, 143, 10.1136/jamia.1999.0060143
Klavans, J.L., Brian W. Extracting taxonomic relationships from online definitional sources using LEXING. In: Proceedings of the First ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL), Roanoke, Virginia; 2001. p. 257–8