dfText classification algorithms for
sports injury prevention
News
2012/05/29 : paper uploaed.
Introduction

It is widely accepted that text categorization techniques can play an important role in systematic review or when collecting scientific evidences for clinical practices. Although text classifiers have been proposed for many medical fields, there are no text classifiers for sports injury prevention. Our research aims to develop classifiers that distinguish original articles about the effectiveness of sports injury preventions from irrelevant articles. Classifiers could also be applied to judge articles for sub-categories among various sports injury preventions such as types of sports, types of injuries, and types of preventions.
Paper
Source codes
 Codes are available here.  One example data can be downloaded from here.  Input files for these codes are provided in PubMed.
Data sets

Data sets were collected from PubMed searching ‘sports injury prevention’. Contact us if you ask something.  For positive samples, original research articles were collected from reference  of seven review articles :  
1. J. Petersen and P. Holmich, Br J Sports Med. 39(6), 319 (2005)
2. S. Aaltonen, H. Karjalainen, A. Heinonen, J. Parkkari, and U. M. Kujala, Arch Intern Med.       167(15), 1585 (2007)
3. J. H. Yoo, B. O. Lim, M. Ha, S. W. Lee, S.J. Oh, Y.S. Lee, and J. G. Kim, Knee Surg Sports      Traumatol Arthrosc. 18(6),  824 (2010)
4. S.B. Thacker, J. Gilchrist, D. F. Stroup, and C. D. Kimsey, Med Sci Sports Exerc. 34(1),           32 (2002)
5. S.M. Weldon, R. H. Hill. Man Ther. 8(3), 141 (2003)
6. S.B. Thacker, J. Gilchrist, D. F. Stroup, and C. D. Kimsey, Jr. Med Sci Sports Exerc. 36(3),       371 (2004)
7. J. Parkkari, U. M. Kujala, and P. Kannus. Sports Med. 31(14), 985 (2001)
Contacts
hyunjulee at gist.ac.kr