Neurolinguistic approach to natural language processing with applications to medical text analysis

Neural Networks

Volumn 21, Issue 10, 2008, Pages 1500-1510

  Duch, Włodzisław ^a,b   Matykiewicz, Paweł ^b,c   Pestian, John ^c  

^a NICOLAUS COPERNICUS UNIVERSITY   (Poland)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c CINCINNATI CHILDREN S HOSPITAL RESEARCH FOUNDATION   (United States)

Author keywords

Medical ontologies; Natural language processing; Semantic networks; Spreading activation networks; Vector models in NLP

Indexed keywords

ARTIFICIAL INTELLIGENCE; CHEMICAL ACTIVATION; COMPUTATIONAL LINGUISTICS; INFORMATION THEORY; LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; NETWORKS (CIRCUITS); ONTOLOGY; SEMANTICS; VECTORS;

MEDICAL ONTOLOGIES; NATURAL LANGUAGE PROCESSING; SEMANTIC NETWORKS; SPREADING ACTIVATION NETWORKS; VECTOR MODELS IN NLP;

NEURAL NETWORKS;

ARTICLE; AUTOMATION; BRAIN CORTEX; BRAIN NERVE CELL; COGNITION; HOSPITAL DISCHARGE; LEARNING; LEFT HEMISPHERE; MEDICAL RECORD; NATURAL LANGUAGE PROCESSING; PRIORITY JOURNAL; RIGHT HEMISPHERE; SEMANTICS; VERBAL COMMUNICATION; WORD RECOGNITION; WRITTEN LANGUAGE;

ALGORITHMS; CLUSTER ANALYSIS; HUMANS; MEDICAL RECORDS SYSTEMS, COMPUTERIZED; NATURAL LANGUAGE PROCESSING; NEUROLINGUISTIC PROGRAMMING; PATIENT DISCHARGE; READING; SEMANTICS; UNIFIED MEDICAL LANGUAGE SYSTEM;

EID: 56949089986     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2008.05.008     Document Type: Article

References (42)

1. Antonie, M. -L., & Zaiane, O. R. (2002). Text document categorization by term association. In Proc. of IEEE int. conf on data mining (pp. 19-26)
2. Bein, W. W., Coombs, J. S., & Taghva, K. (2003). A method for calculating term similarity on large document collections. In Int. conf. on information technology: Computers and communications (pp. 199-207)
3. Bowden E.M., Jung-Beeman M., Fleck J., and Kounios J. New approaches to demystifying insight. Trends in Cognitive Science 9 (2005) 322-328
4. Brock, G., Pihur, V., Datta, S., & Datta, S. See http://cran.r-project.org/src/contrib/Descriptions/clValid.html
5. Cimiano P. Ontology learning and population from text. Algorithms, evaluation and applications (2006), Springer
6. Crestani F. Application of spreading activation techniques in information retrieval. Artificial Intelligence Review 11 (1997) 453-482
7. Crestani F., and Lee P.L. Searching the web by constrained spreading activation. Information Processing & Management 36 (2000) 585-605
8. Dehaene S., Cohen L., Sigman M., and Vinckier F. The neural code for written words: A proposal. Trends in Cognitive Science 9 (2005) 335-341
9. Dehaene S., and Naccache L. Towards a cognitive neuroscience of consciousness: Basic evidence and a workspace framework. Cognition 79 (2001) 1-37
10. Duch W. Brain-inspired conscious computing architecture. Journal of Mind and Behavior 26 1-2 (2005) 1-22
11. Duch W. Filter Methods. In: Guyon I., Gunn S., Nikravesh M., and Zadeh L. (Eds). Feature extraction, foundations and applications. Studies in fuzziness and soft computing (2006), Physica-Verlag, Springer 89-118
12. Duch W. Creativity and the brain. In: Tan A.-G. (Ed). A handbook of creativity for teachers (2007), World Scientific Publishing, Singapore 507-530
13. Duch W., and Diercksen G.H.F. Feature space mapping as a universal adaptive system. Computer Physics Communications 87 (1995) 341-371
14. Duch W., and Pilichowski M. Experiments with computational creativity. Neural Information Processing - Letters and Reviews 11 (2007) 123-133
15. Gaillard R., Naccache L., Pinel P., Clémenceau S., Volle E., Hasboun D., et al. Direct intracranial, FMRI, and lesion evidence for the causal role of left inferotemporal cortex in reading. Neuron 50 (2006) 19-204
16. Ghostminer data mining software. www.fqspl.com.pl/ghostminer/
17. Gra{ogonek}bczewski, K., & Duch, W. (2000). The separability of split value criterion. In 5th conf. on neural networks and soft computing (pp. 201-208)
18. Gruszka A., and Ncka E. Priming and acceptance of close and remote associations by creative and less creative people. Creativity Research Journal 14 (2002) 193-205
19. Itert L., Duch W., and Pestian J. Influence of a priori knowledge on medical document categorization. IEEE symposium on computational intelligence in data mining (2007), IEEE Press 163-170
20. Jung-Beeman M., Bowden E.M., Haberman J., Frymiare J.L., Arambel-Liu S., Greenblatt R., et al. Neural activity when people solve verbal problems with insight. PLoS Biology 2 (2004) 500-510
21. Just M.A., and Varma S. The organization of thinking: What functional brain imaging reveals about the neuroarchitecture of complex cognition. Cognitive, Affective, & Behavioral Neuroscience 7 3 (2007) 153-191
22. Lamb S. Pathways of the brain: The neurocognitive basis of language (1999), J. Benjamins Publishing Co, Amsterdam & Philadelphia
23. In: Lehmann F. (Ed). Semantic networks in artificial intelligence (1992), Pergamon, Oxford
24. Lin L., Osan R., and Tsien J.Z. Organizing principles of real-time memory encoding: Neural clique assemblies and universal neural codes. Trends in Neuroscience 29 1 (2006) 48-57
25. Li Y., Zuhair A.B., and McLean D. An approach for measuring semantic similarity between words using multiple information sources. IEEE Transactions on Knowledge and Data Engineering 15 4 (2003) 871-882
26. Manning C.D., and Schütze H. Foundations of statistical natural language processing (1999), MIT Press, Cambridge, MA
27. Matykiewicz P., Duch W., and Pestian J. Nonambiguous concept mapping in medical domain. Lecture notes in artificial intelligence Vol. 4029 (2006) 941-950
28. Medical subject headings, MeSH, National Library of Medicine, URL: http://www.nlm.nih.gov/mesh/
29. Mednick S.A. The associative basis of the creative process. Psychological Review 69 (1962) 220-232
30. MetaMap, Available at http://mmtx.nlm.nih.gov
31. Miikkulainen R. Subsymbolic natural language processing: An integrated model of scripts, lexicon, and memory (1993), MIT Press, Cambridge, MA
32. Miikkulainen R. Text and discourse understanding: The DISCERN system. In: Dale R., Moisl H., and Somers H. (Eds). A handbook of natural language processing: Techniques and applications for the processing of language as text (2002), Marcel Dekker, New York 905-919
33. Pe{ogonek}kalska E., and Duin R.P.W. The dissimilarity representation for pattern recognition: Foundations and applications (2005), World Scientific, New Jersey; London
34. Pestian, J., Aronow, B., & Davis, K. (2002). Design and data collection in the discovery system. In Int. conf. on mathematics and engineering techniques in medicine and biological science
35. Pulvermuller F. The neuroscience of language. On brain circuits of words and serial order (2003), Cambridge University Press, Cambridge, UK
36. Rousseeuw P.J. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computationa; Applied Mathematics 20 (1987) 53-65
37. In: Rumelhart D.E., and McClelland J.L. (Eds). Parallel distributed processing: Explorations in the microstructure of cognition vol. 1: Foundations, vol. 2: Psychological and biological models (1986), MIT Press, Cambridge, MA
38. In: Sowa J.F. (Ed). Principles of semantic networks: Explorations in the representation of knowledge (1991), Morgan Kaufmann Publishers, San Mateo, CA
39. Tsatsaronis, G., Vazirgiannis, M., & Androutsopoulos, I. (2007). Word sense disambiguation with spreading activation networks generated from thesauri. In 20th Int. Joint Conf. in Artificial Intelligence (pp. 1725-1730)
40. UMLS Knowledge Sources, 13th Edition-January Release. Available http://www.nlm.nih.gov/research/umls
41. Ward J.H. Hierachical grouping to optimize an objective function. Journal of American Statistical Association 58 (1963) 236-244
42. Zhou, X., Zhang, X., & Hu, X. (2007). Semantic smoothing of document models for agglomerative clustering, In 20th int. joint conf. on artificial intelligence(pp. 2922-2927)