It is increasingly common to have medical information in electronic format. This includes scientific articles as well as clinical management reviews, and even records from health institutions with patient data. However, traditional instruments, both individual and institutional, are of little use for selecting the most appropriate information in each case, either in the clinical or research field. So-called text or data «mining» enables this huge amount of information to be managed, extracting it from various sources using processing systems (filtration and curation), integrating it and permitting the generation of new knowledge. This review aims to provide an overview of text and data mining, and of the potential usefulness of this bioinformatic technique in the exercise of care in respiratory medicine and in research in the same field.
Keywords: Chronic obstructive pulmonary disease; Critically ill respiratory patients; Cáncer de pulmón; Enfermedad pulmonar obstructiva crónica; Enfermedades respiratorias; Lung cancer; Minería de textos; Paciente respiratorio crítico; Respiratory diseases; Text mining.
Copyright © 2013 SEPAR. Published by Elsevier Espana. All rights reserved.