Publikation
Text mining-based measurement of precision of polysomnographic reports as basis for intervention.
Wissenschaftlicher Artikel/Review - 31.01.2022
Baty Florent, Hegermann Jemima, Locatelli Tiziana, Rüegg Claudio, Gysin Christian, Rassouli Frank, Brutsche Martin
Bereiche
PubMed
DOI
Kontakt
Zitation
Art
Zeitschrift
Veröffentlichungsdatum
eISSN (Online)
Seiten
Kurzbeschreibung/Zielsetzung
Text mining can be applied to automate knowledge extraction from unstructured data included in medical reports and generate quality indicators applicable for medical documentation. The primary objective of this study was to apply text mining methodology for the analysis of polysomnographic medical reports in order to quantify sources of variation - here the diagnostic precision vs. the inter-rater variability - in the work-up of sleep-disordered breathing. The secondary objective was to assess the impact of a text block standardization on the diagnostic precision of polysomnography reports in an independent test set.