Deep Learning Predicts HPV Association in Oropharyngeal Squamous Cell Carcinomas and Identifies Patients with a Favorable Prognosis Using Regular H&E Stains.

Sebastian KleinAlexander QuaasJennifer QuantiusHeike LöserJörn MeinelMartin PeiferSteffen WagnerStefan GattenlöhnerClaus WittekindtMagnus von Knebel-DoeberitzElena-Sophie PriggeChristine LangerKa-Won NohMargaret MaltsevaHans Christian ReinhardtReinhard BüttnerJens Peter Klußmann Nora Wuerdemann

Published in: Clinical cancer research : an official journal of the American Association for Cancer Research (2020)

Detection of HPV association in OPSCC using deep learning with help of regular H&E stains may either be used as a single biomarker, or in combination with p16 status, to identify patients with OPSCC with a favorable prognosis, potentially outperforming combined HPV-DNA/p16 status as a biomarker for patient stratification.

Keyphrases

deep learning
high grade
squamous cell
artificial intelligence
convolutional neural network
machine learning
cervical cancer screening
case report
circulating tumor
genome wide
single molecule
circulating tumor cells
sensitive detection