Multi-field-of-view deep learning model predicts nonsmall cell lung cancer programmed death-ligand 1 status from whole-slide hematoxylin and eosin images

Multi-field-of-view deep learning model predicts nonsmall cell lung cancer programmed death-ligand 1 status from whole-slide hematoxylin and eosin images

Background: Tumor programmed death-ligand 1 (PD-L1) status is useful in determining which patients may benefit from programmed death-1 (PD-1)/PD-L1 inhibitors. However, little is known about the association between PD-L1 status and tumor histopathological patterns. Using deep learning, we predicted...

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Bibliographic Details
Main Authors: Lingdao Sha, Boleslaw L Osinski, Irvin Y Ho, Timothy L Tan, Caleb Willis, Hannah Weiss, Nike Beaubier, Brett M Mahon, Tim J Taxter, Stephen S F Yip
Format: Article
Language:English
Published: Elsevier 2019-01-01
Series:Journal of Pathology Informatics
Subjects:
Artificial intelligence
deep learning
digital pathology
lung cancer
Online Access:http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2019;volume=10;issue=1;spage=24;epage=24;aulast=Sha

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