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- Title
VP05.03: Machine learning in the detection of forniceal endometriosis.
- Authors
Guerriero, S.; Pascual, M.; Ajossa, S.; Graupera, B.; Rodríguez, I.; Pagliuca, M.; Deiala, F.; Alcazar, J.
- Abstract
The aim of this study was to compare the accuracy of seven classical machine learning (ML) models trained with ultrasound (US) soft markers to raise suspicion of forniceal endometriotic involvement. Methods Input data to the models was retrieved from a database of 194 patients submitted to surgery for the suspicion of presence of deep endometriosis. All models were trained on the training dataset and the predictions have been evaluated using the test dataset.
- Subjects
MACHINE learning; ENDOMETRIOSIS; ARTIFICIAL intelligence
- Publication
Ultrasound in Obstetrics & Gynecology, 2021, Vol 58, p112
- ISSN
0960-7692
- Publication type
Article
- DOI
10.1002/uog.24088