Exploiting the systematic review protocol for classification of medical abstracts

Artificial Intelligence in Medicine

Volumn 51, Issue 1, 2011, Pages 17-25

  Frunza, Oana ^a   Inkpen, Diana ^a   Matwin, Stan ^a   Klement, William ^a   O'Blenis, Peter ^b  

^a UNIVERSITY OF OTTAWA   (Canada)

^b Evidence Partners Corporation   (Canada)

Author keywords

Automatic text classification; Ensemble of classifiers; Medical concepts; Systematic reviews for the medical domain; Text representation

Indexed keywords

AUTOMATIC TEXT CLASSIFICATION; ENSEMBLE OF CLASSIFIERS; MEDICAL CONCEPTS; SYSTEMATIC REVIEW; TEXT REPRESENTATION;

ABSTRACTING; CLASSIFIERS; HEALTH CARE; INFORMATION RETRIEVAL SYSTEMS; LEARNING ALGORITHMS; LOCOMOTIVES; MANAGEMENT; RAILROAD CARS;

TEXT PROCESSING;

ACCURACY; ARTICLE; AUTOMATION; BAYESIAN LEARNING; CLASSIFICATION ALGORITHM; MACHINE LEARNING; MEDICAL DOCUMENTATION; PRIORITY JOURNAL; SYSTEMATIC REVIEW (TOPIC); WORKFLOW;

ABSTRACTING AND INDEXING AS TOPIC; AGED; AGED, 80 AND OVER; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIBLIOMETRICS; DATA MINING; DATABASES, BIBLIOGRAPHIC; EVIDENCE-BASED MEDICINE; HEALTH SERVICES FOR THE AGED; HUMANS; PATTERN RECOGNITION, AUTOMATED; PUBLICATIONS; REVIEW LITERATURE AS TOPIC; WORKFLOW;

EID: 78650931886     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2010.10.005     Document Type: Article

References (16)

1. Cohen A.M., Hersh W.R., Peterson K., Yen P.Y. Reducing workload in systematic review preparation using automated citation classification. Journal of the American Medical Informatics Association 2006, 13:206-219.
2. Aphinyanaphongs Y., Aliferis C. Text categorization models for retrieval of high quality articles. Journal of the American Medical Informatics Association 2005, 12:207-216.
3. Haynes R.B., Wilczynski N., McKibbon K.A., Walker C.J., Sinclair J.C. Developing optimal search strategies for detecting clinically sound studies in MEDLINE. Journal of the American Medical Informatics Association 1994, 1:447-458.
4. Kohavi R., Provost F. Glossary of terms. Machine Learning 1998, 30:271-274.
5. Witten IH, Frank E. Data mining: practical machine learning tools and techniques, 2nd ed. Morgan Kaufmann, San Francisco; 2005. [accessed 24.09.08]. http://www.cs.waikato.ac.nz/machine%20learning/weka/.
6. Ma Y. Text classification on imbalanced data: application to systematic reviews automation, M.Sc. thesis, University of Ottawa; 2007.
7. Quinlan J.R. Induction on decision trees. Machine Learning 1986, 1:81-106.
8. Yang Y., Pedersen J. A comparative study on feature selection in text categorization. ICML '97: proceedings of the fourteenth international conference on machine learning 1997, 412-420.
9. Forman G. Choose your words carefully: an empirical study of feature selection metrics for text classification. Proceedings of the 6th European conference on principals of data mining and knowledge discovery 2002, 150-162. Springer-Verlag, London, England.
10. National Library of Medicine, Unified medical language system fact sheet. Available at [accessed 24.09.08]. http://www.nlm.nih.gov/pubs/factsheets/umls.html.
11. National Library of Medicine. MetaMap. Available at: [accessed 24.09.08]. http://mmtx.nlm.nih.gov/.
12. Cohen A.M., Hersh W.R., Bhupatiraju R.T. Feature generation, feature selection, classifiers, and conceptual drift for biomedical document triage. Proceedings of the thirteenth text retrieval conference 2004, National Institute of Standards and Technology, Gaithersburg, MD.
13. Frank E., Bouckaert R.R. Naive Bayes for text classification with unbalanced classes. Proceedings of the 10th European conference on principles and practice of knowledge discovery in databases 2006, 503-510. Springer, Berlin.
14. Colas F., Brazdil P. Comparison of SVM and some older classification algorithms. Text classification tasks: artificial intelligence in theory and practice 2006, 217. Springer, Boston, p. 169-78.
15. Dietterich T. Machine-learning research: four current directions. Artificial Intelligence 1997, 18:97-136.
16. Kouznetsov A., Matwin S., Inkpen D., Razavi A., Frunza O., Sehatkar M., et al. Classifying biomedical abstracts using committees of classifiers and collective ranking techniques. The 22nd Canadian conference on artificial intelligence 2009, 224-228. Springer, Berlin.