Multilingual chief complaint classification for syndromic surveillance: An experiment with Chinese chief complaints

International Journal of Medical Informatics

Volumn 78, Issue 5, 2009, Pages 308-320

  Lu, Hsin Min ^a   Chen, Hsinchun ^a   Zeng, Daniel ^a,d   King, Chwan Chuen ^b   Shih, Fuh Yuan ^c   Wu, Tsung Shu ^b   Hsiao, Jin Yi ^b  

^a UNIVERSITY OF ARIZONA   (United States)

^b NATIONAL TAIWAN UNIVERSITY   (Taiwan)

^c NATIONAL TAIWAN UNIVERSITY HOSPITAL   (Taiwan)

^d INSTITUTE OF AUTOMATION   (China)

Author keywords

Communicable disease control; Medical records; Multilingual chief complaint classification; Statistical pattern extraction; Syndromic surveillance

Indexed keywords

COMMUNICABLE DISEASE CONTROL; MEDICAL RECORDS; MULTILINGUAL CHIEF COMPLAINT CLASSIFICATION; STATISTICAL PATTERN EXTRACTION; SYNDROMIC SURVEILLANCE;

COMPUTER AIDED LANGUAGE TRANSLATION; DISEASE CONTROL; INFORMATION THEORY; LINGUISTICS; SECURITY OF DATA; SPEECH TRANSMISSION; TRANSLATION (LANGUAGES);

TEXT PROCESSING;

ARTICLE; CHINESE; DATA ANALYSIS; ENGLISH AS A SECOND LANGUAGE; EPIDEMIC; HEALTH SURVEY; HUMAN; INFORMATION PROCESSING; LANGUAGE; PREDICTION AND FORECASTING; PRIORITY JOURNAL; PUBLIC HEALTH SERVICE; SATISFACTION; SENSITIVITY ANALYSIS; SYNDROMIC SURVEILLANCE;

CHINA; DISEASE OUTBREAKS; HUMANS; LANGUAGE; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SENTINEL SURVEILLANCE;

EID: 62849086564     PISSN: 13865056     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijmedinf.2008.08.004     Document Type: Article

References (51)

1. Liang H., and Xue Y. Investigating public health emergency response information system initiatives in China. Int. J. Med. Inf. 73 (2004) 675-685
2. Bellika J.G., Hasvold T., and Hartvigsen G. Propagation of program control: a tool for distributed disease surveillance. Int. J. Med. Inf. 76 (2006) 313-329
3. Chapman W.W., Dowling J.N., and Wagner M.M. Generating a reliable reference standard set for syndromic case classification. J. Am. Med. Inf. Assoc. 12 6 (2005) 618-629
4. Chapman W.W., Christensen L.M., Wagner M.M., Haug P.J., Ivanov O., Dowling J.N., et al. Classifying free-text triage chief complaints into syndromic categories with natural language processing. Artif. Intell. Med. 33 1 (2005) 31-40
5. Ivanov O., Wagner M.M., Chapman W.W., and Olszewski R.T. Accuracy of three classifiers of acute gastrointestinal syndrome for syndromic surveillance. AMIA Symposium (2002) 345-349
6. Espino J.U., and Wagner M.M. The accuracy of ICD-9 coded chief complaints for detection of acute respiratory illness. Proceedings of the AMIA Annual Symposium (2001) 164-168
7. Marko K., Schulz S., and Hahn U. Automatic lexeme acquisition for a multilingual medical subword thesaurus. Int. J. Med. Inf. 76 2-3 (2007) 184-189
8. Olszewski R.T. Bayesian classification of triage diagnoses for the early detection of epidemics. FLAIRS Conference. Menlo Park, California (2003) 412-416
9. Espino J.U., Dowling J., Levander J., Sutovsky P., Wagner M.M., and Copper G.F. SyCo: a probabilistic machine learning method for classifying chief complaints into symptom and syndrome categories. Syndromic Surveillance Conference. Baltimore, Maryland (2006)
10. Sadeghi S., Barzi A., Sadeghi N., and King B. A Bayesian model for triage decision support. Int. J. Med. Inf. 75 5 (2006) 403-411
11. Lu H.-M., Zeng D., and Chen H. Ontology-enhanced Automatic Chief Complaint Classification for Syndromic Surveillance. J. Biomed. Inf. 41 2 (2008) 340-356
12. Lu H.-M., Zeng D., and Chen H. Ontology-based automatic chief complaints classification for syndromic surveillance. IEEE International Conference on Systems, Man, and Cybernetics. Taipei, Taiwan (2006)
13. van Rijsbergen C.J. Information Retrieval (1979), Butterworths, London
14. Pakhomov S.V.S., Buntrock J.D., and Chute C.G. Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques. J. Am. Med. Inf. Assoc. 13 (2006) 516-525
15. Hutwagner L., Thompson W., Seeman G.M., and Treadwell T. The bioterrorism preparedness and response early aberration reporting system (EARS). J. Urban Health 80 2 Suppl. 1 (2003) i89-i96
16. T.-S. Wu, Establishing emergency department-based infectious disease syndromic surveillance system in Taiwan-aberration detection methods, epidemiological characteristics, system evaluation and recommendations. Master Thesis, National Taiwan University, 2005.
17. Wu T.-S., Shih F.-Y., Yen M.-Y., Wu J.-S., Lu S.-W., Chang K., et al. Establishing a nationwide emergency department-based syndromic surveillance system for better public health responses in Taiwan. BMC Public Health 8 1 (2008) 18
18. Fisher F.S., Whaley F.S., Krushat W.M., Malenka D.J., Fleming C., Baron J.A., et al. The accuracy of Medicare's hospital claims data: progress has been made, but problems remain. Am. J. Public Health 82 2 (1999) 243-248
19. Day F.C., Schriger D.L., and La M. Automated linking of free-text complaints to Reason-for-Visit categories and International Classification of Diseases diagnoses in emergency department patient record databases. Ann. Emerg. Med. 43 3 (2004) 401-409
20. Li K.W., and Yang C.C. Conceptual analysis of parallel corpus collected from the web. J. Am. Soc. Inf. Sci. Technol. 57 5 (2006) 632-644
21. Qin J., Zhou Y., Chau M., and Chen H. Multilingual web retrieval: an experiment in English-Chinese business intelligence. J. Am. Soc. Inf. Sci. Technol. 57 5 (2006) 671-683
22. Chen H.-H. Cross-language information retrieval: theories and technologies. J. Libr. Inf. Sci. 28 1 (2002) 19-32
23. Arnold D., Balkan L., Meijer S., Humphreys R., and Sadler L. Machine Translation: An Introductory Guide (1994), Blackwells-NCC, London
24. Sakai T. MT-based Japanese-English cross-language IR experiments using the TREC test collections. Fifth International Workshop on Information Retrieval with Asian Language. Hong Kong, China (2000)
25. Oard D.W. Adaptive Vector Space Text Filtering for Monolingual and Cross-Language Applications (1996), University of Maryland, College Park
26. Brown R.D. Example-based machine translation in the Pangloss system. Proceedings of the 16th International Conference on Computational Linguistics (COLING-96). Copenhagen, Denmark (1996) 169-174
27. Talvensaari T., Juhola M., Laurikkala J., and Jarvelin K. Corpus-based cross-language information retrieval in retrieval of highly relevant documents. J. Am. Soc. Inf. Sci. Technol. 58 3 (2007) 322-334
28. Daumke P., Marku K., Poprat M., Schulz S., and Klar R. Biomedical information retrieval across languages. Inf. Health Social Care 32 2 (2007) 131-147
29. Pirkola A., Hedlund T., Keskustalo H., and Jarvelin K. Dictionary-based cross-language information retrieval: problems, methods, and research findings. Inf. Retrieval 4 3-4 (2001) 209-230
30. Aljlayl M., Frieder O., and Grossman D. On bidirectional English-Arabic search. J. Am. Soc. Inf. Sci. Technol. 53 13 (2002) 1139-1151
31. Teahan W.J., Wen Y., McNab R., and Witten I.H. A compression-based algorithm for Chinese word segmentation. Computat. Linguistics 26 3 (2001) 375-393
32. Ng H.T., and Low J.K. Chinese part-of-speech tagging: one-at-a-time or all-at-once? Word-based or character-based?. Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP 2004). Barcelona, Spain (2004) 277-284
33. Manning C., and Schütze H. Foundations of Statistical Natural Language Processing (1999), MIT Press, Cambridge, MA
34. Sproat R., and Shin C.L. A statistical method for finding word boundaries in Chinese text. Comput. Process. Chin. Oriental Lang. 4 4 (1990) 336-351
35. Yang C.C., Luk J.W.K., Yung S.K., and Yen J. Combination and boundary detection approaches on Chinese indexing. J. Am. Soc. Inf. Sci. 51 4 (2000) 340-351
36. Wang J. Automatic thesaurus development: term extraction from title metadata. J. Am. Soc. Inf. Sci. Technol. 57 7 (2006) 907-920
37. Chien L.-F. PAT-tree-based adaptive keyphrase extraction for intelligent Chinese information retrieval. Inf. Process. Manag. 35 4 (1999) 501-521
38. Cheng K.S., Young G.H., and Wong K.F. A study on word-based and integral-bit Chinese text compression algorithm. J. Am. Soc. Inf. Sci. 50 3 (1999) 218-228
39. Wu Z., and Tseng G. Chinese text segmentation for text retrieval: achievements and problems. J. Am. Soc. Inf. Sci. 44 9 (1993) 532-542
40. Goh C.L., Asahara M., and Matsumoto Y. Chinese word segmentation by classification of characters. Comput. Ling. Chin. Lang. Process. 10 3 (2005) 381-396
41. Cleary J.G., and Witten I.H. Data compression using adaptive coding and partial string matching. IEEE Trans. Commun. 32 4 (1984) 396-402
42. Wang F.L., and Yang C.C. Mining web data for Chinese segmentation. J. Am. Soc. Inf. Sci. Technol. 58 12 (2007) 1820-1837
43. Ong T.-H., and Chen H. Updateable PAT-Tree approach to Chinese key phrase extraction using mutual information: a linguistic foundation for knowledge management. Proceedings of the Second Asian Digital Library Conference. Taipei, Taiwan (1999)
44. Gonnet G.H., Baeza-Yates R., and Snider T. New indices for text: PAT Trees and PAT arrays. Information Retrieval: Data Structures and Algorithms (1992), Prentice-Hall pp. 66-82
45. Travers D.A., and Haas S.W. Evaluation of emergency medical text processor, a system for cleaning chief complaint textual data. Acad. Emerg. Med. 11 11 (2004) 1170-1176
46. Travers D.A., and Haas S.W. Using nurses' natural language entries to build a concept-oriented terminology for patients' chief complaints in the emergency department. J. Biomed. Inf. 36 (2003) 260-270
47. Gesteland P.H., Gardner R.M., Tsui F.-C., Espino J.U., Rolfs R.T., James B.C., et al. Automated syndromic surveillance for the 2002 winter Olympics. J. Am. Med. Inf. Assoc. 10 November/December (6) (2003) 547-554
48. Fleiss J.L. Statistical Methods for Rates and Proportions. second ed. (1981), John Wiley & Sons, NY, NY
49. NIST, NIST 2006 Machine Translation Evaluation Official Results, 2006 (cited 2007 July 2), available from: http://www.itl.nist.gov/iad/894.01/tests/mt/doc/mt06eval_official_results.html.
50. Agresti A. Categorical Data Analysis (2002), John Wiley & Sons, Hoboken, New Jersey
51. McNemar Q. Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika 12 (1947) 153-157