Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks

Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks

Abstract Background Ovarian cancer causes 151,900 deaths per year worldwide. Treatment and prognosis are primarily determined by the histopathologic interpretation in combination with molecular diagnosis. However, the relationship between histopathology patterns and molecular alterations is not full...

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Bibliographic Details
Main Authors: Kun-Hsing Yu, Vincent Hu, Feiran Wang, Ursula A. Matulonis, George L. Mutter, Jeffrey A. Golden, Isaac S. Kohane
Format: Article
Language:English
Published: BMC 2020-08-01
Series:BMC Medicine
Subjects:
Digital pathology
Platinum response
Gene expression
Proteomics
Machine learning
Serous ovarian carcinoma
Online Access:http://link.springer.com/article/10.1186/s12916-020-01684-w

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http://link.springer.com/article/10.1186/s12916-020-01684-w

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