Automatic retrieval of current evidence to support update of bibliography in clinical guidelines

Authors:
A. Iruetaguena;J. J. Garcia Adeva;J. M. Pikatza;U. Segundo;D. Buenestado;R. Barrena
Affiliations:
Department of Computer Languages and Systems, Faculty of Informatics, University of the Basque Country UPV/EHU, Paseo Manuel de Lardizabal 1, 20018 Donostia, Spain;Department of Computer Languages and Systems, Faculty of Informatics, University of the Basque Country UPV/EHU, Paseo Manuel de Lardizabal 1, 20018 Donostia, Spain;Department of Computer Languages and Systems, Faculty of Informatics, University of the Basque Country UPV/EHU, Paseo Manuel de Lardizabal 1, 20018 Donostia, Spain;Department of Computer Languages and Systems, Faculty of Informatics, University of the Basque Country UPV/EHU, Paseo Manuel de Lardizabal 1, 20018 Donostia, Spain;Department of Computer Languages and Systems, Faculty of Informatics, University of the Basque Country UPV/EHU, Paseo Manuel de Lardizabal 1, 20018 Donostia, Spain;Department of Computer Languages and Systems, Faculty of Informatics, University of the Basque Country UPV/EHU, Paseo Manuel de Lardizabal 1, 20018 Donostia, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2013

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Abstract

This paper reports on a system developed to support medical experts in the process of updating clinical guidelines by automatically suggesting new articles suitable to the domain under consideration. It follows a comprehensive process based on several consecutive steps in order to (i) identify which articles from the current guideline are eligible to be updated; (ii) retrieve and filter new related articles from medline; and (iii) select the most relevant resulting articles by applying a scoring algorithm. Extensive validation is based on a set of experiments on 40 guidelines from multiple medical domains. The analysis of results shows a promising prospect as indicated by recall values greater than 90%.