Towards ontology-based decision support systems for complex ultrasound diagnosis in obstetrics and gynecology - 15/12/17
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Abstract |
Introduction |
We have developed a new knowledge base intelligent system for obstetrics and gynecology ultrasound imaging, based on an ontology and a reference image collection. This study evaluates the new system to support accurate annotations of ultrasound images. We have used the early ultrasound diagnosis of ectopic pregnancies as a model clinical issue.
Material and methods |
The ectopic pregnancy ontology was derived from medical texts (4260 ultrasound reports of ectopic pregnancy from a specialist center in the UK and 2795 Pubmed abstracts indexed with the MeSH term “Pregnancy, Ectopic”) and the reference image collection was built on a selection from 106 publications. We conducted a retrospective analysis of the signs in 35 scans of ectopic pregnancy by six observers using the new system.
Results |
The resulting ectopic pregnancy ontology consisted of 1395 terms, and 80 images were collected for the reference collection. The observers used the knowledge base intelligent system to provide a total of 1486 sign annotations. The precision, recall and F-measure for the annotations were 0.83, 0.62 and 0.71, respectively. The global proportion of agreement was 40.35% 95% CI [38.64–42.05].
Discussion |
The ontology-based intelligent system provides accurate annotations of ultrasound images and suggests that it may benefit non-expert operators. The precision rate is appropriate for accurate input of a computer-based clinical decision support and could be used to support medical imaging diagnosis of complex conditions in obstetrics and gynecology.
Le texte complet de cet article est disponible en PDF.Keywords : Ectopic pregnancy, Ultrasound imaging, Image annotations, Knowledge base, Ontology, Decision support system
Plan
Vol 46 - N° 5
P. 423-429 - mai 2017 Retour au numéroBienvenue sur EM-consulte, la référence des professionnels de santé.
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