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 o...
| Publicado en: | Journal of Telemedicine & Telecare Vol. 14; no. 7; pp. 354 - 359 |
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| Autores principales: | , , |
| Formato: | research Journal Article |
| Publicado: |
Sage Publications Inc.
Oct2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | 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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