Deep neural network classification based on somatic mutations potentially predicts clinical benefit of immune checkpoint blockade in lung adenocarcinoma

Deep neural network classification based on somatic mutations potentially predicts clinical benefit of immune checkpoint blockade in lung adenocarcinoma

Although several biomarkers have been proposed to predict the response of patients with lung adenocarcinoma (LUAD) to immune checkpoint blockade (ICB) therapy, existing challenges such as test platform uniformity, cutoff value definition, and low frequencies restrict their effective clinical applica...

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Bibliographic Details
Main Authors: Jie Peng, Dan Zou, Wuxing Gong, Shuai Kang, Lijie Han
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:OncoImmunology
Subjects:
lung adenocarcinoma
immune checkpoint blockade
deep neural networks
somatic mutations
Online Access:http://dx.doi.org/10.1080/2162402X.2020.1734156

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