Machine learning and radiomics for segmentation and classification of adnexal masses on ultrasound

Machine learning and radiomics for segmentation and classification of adnexal masses on ultrasound

Abstract Ultrasound-based models exist to support the classification of adnexal masses but are subjective and rely upon ultrasound expertise. We aimed to develop an end-to-end machine learning (ML) model capable of automating the classification of adnexal masses. In this retrospective study, transva...

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Bibliographic Details
Main Authors: Jennifer F. Barcroft, Kristofer Linton-Reid, Chiara Landolfo, Maya Al-Memar, Nina Parker, Chris Kyriacou, Maria Munaretto, Martina Fantauzzi, Nina Cooper, Joseph Yazbek, Nishat Bharwani, Sa Ra Lee, Ju Hee Kim, Dirk Timmerman, Joram Posma, Luca Savelli, Srdjan Saso, Eric O. Aboagye, Tom Bourne
Format: Article
Language:English
Published: Nature Portfolio 2024-02-01
Series:npj Precision Oncology
Online Access:https://doi.org/10.1038/s41698-024-00527-8

Internet

https://doi.org/10.1038/s41698-024-00527-8

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