VP03.02: A machine learning approach applied to gynecological ultrasound to predict progression‐free survival in ovarian cancer patients

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Published in:Ultrasound in obstetrics & gynecology 2021-10, Vol.58 (S1), p.99-100
Main Authors: Arezzo, F., Loizzi, V., Lombardi, C., Cazzato, G., Venerito, V., Cataldo, V., Mongelli, M., Cicinelli, E., Cormio, G., Santarsiero, C.
Format: Article
Language:English
Subjects:
Learning algorithms
Machine learning
Ovarian cancer
Ultrasonic imaging
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container_end_page 100
container_issue S1
container_start_page 99
container_title Ultrasound in obstetrics & gynecology
container_volume 58
creator Arezzo, F.
Loizzi, V.
Lombardi, C.
Cazzato, G.
Venerito, V.
Cataldo, V.
Mongelli, M.
Cicinelli, E.
Cormio, G.
Santarsiero, C.
description
doi_str_mv 10.1002/uog.24046
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1469-0705
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source Wiley-Blackwell Read & Publish Collection
subjects Learning algorithms
Machine learning
Ovarian cancer
Ultrasonic imaging
title VP03.02: A machine learning approach applied to gynecological ultrasound to predict progression‐free survival in ovarian cancer patients
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