NDLI: Classification of PICO elements by text features systematically extracted from PubMed abstracts

Content Provider	IEEE Xplore Digital Library
Author	Ke-Chun Huang Liu, C.C.-H. Shung-Shiang Yang Chun-Chih Liao Xiao, F. Jau-Min Wong I-Jen Chiang
Copyright Year	2011
Description	Author affiliation: National Taiwan University Hospital, Taipei, Taiwan (Chun-Chih Liao; Xiao, F.) \|\| Graduate Institute of Medical Informatics, Taipei Medical University, Taipei, Taiwan (I-Jen Chiang) \|\| Graduate Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan (Ke-Chun Huang; Liu, C.C.-H.; Shung-Shiang Yang) \|\| Department of Health, Taipei Hospital, Taipei, Taiwan (Jau-Min Wong)
Abstract	We propose and evaluate a systematic approach to detect and classify Patient/Problem, Intervention, Comparison and Outcome (PICO) from the medical literature. The training and test corpora were generated systematically and automatically from structured PubMed abstracts. 23,472 sentences by exact pattern match of head words of P-I-O categories. Afterward, the terms with top frequencies were used as the features of Naïve Bayesian classifier. This approach achieves F-measure values of 0.91 for Patient/Problem, 0.75 for Intervention and 0.88 for Outcome, comparable to previous studied based on mixed textural, paragraphical, and semantic features. In conclusion, we show that by stricter pattern matching criteria of training set, detection and classification of PICO elements can be reproducible with minimal expert intervention. The results of this work are higher than previous studies.
Starting Page	279
Ending Page	283
File Size	291416
Page Count	5
File Format	PDF
ISBN	9781457703720
e-ISBN	9781457703713
DOI	10.1109/GRC.2011.6122608
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-08
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training information extraction Bayesian methods natural language processing Knowledge based systems question answering Abstracts text mining Informatics Pattern matching Testing
Content Type	Text
Resource Type	Article

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