A method of extracting the number of trial participants from abstracts describing randomized controlled trials.
We have developed a method for extracting the number of trial participants from abstracts describing randomized controlled trials (RCTs); the number of trial participants may be an indication of the reliability of the trial. The method depends on statistical natural language processing. The number of interest was determined by a binary supervised classification based on a support vector machine algorithm. The method was trialled on 223 abstracts in which the number of trial participants was identified manually to act as a gold standard. Automatic extraction resulted in 2 false-positive and 19 false-negative classifications. The algorithm was capable of extracting the number of trial participants with an accuracy of 97% and an F-measure of 0.84. The algorithm may improve the selection of relevant articles in regard to question-answering, and hence may assist in decision-making.
Hansen
Marie J
MJ
Aalborg University, Aalborg, Denmark. mjha03@hst.aau.dk
Rasmussen
Nana Ø
NØ
Chung
Grace
G
D000465:Algorithms; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D009323:Natural Language Processing; D018579:Patient Selection; D016032:Randomized Controlled Trials as Topic; D012107:Research Design