Journal of Telemedicine and Telecare > Volume 14, Number 7 > Pp. 354-358

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RESEARCH Original articles

A method of extracting the number of trial participants from abstracts describing randomized controlled trials

Marie J Hansen ^* , Nana Ø Rasmussen ^* and Grace Chung 

^* Aalborg University, Aalborg, Denmark; University of New South Wales, Sydney, NSW, Australia

Correspondence: Marie Juul Hansen, Øster Havnegade 8, st.th, 9000 Aalborg, Denmark (Email: mjha03{at}hst.aau.dk)

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.

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