Assessing PD-L1 expression in non-small cell lung cancer and predicting responses to immune checkpoint inhibitors using deep learning on computed tomography images
Panwen Tian, Bingxi He, Wei Mu, Kunqin Liu, Li Liu, Hao Zeng, Yujie Liu, Lili Jiang, Ping Zhou, Zhipei Huang, Di Dong, Weimin Li
Abstract
The deep learning model provides a noninvasive method to predict high PD-L1 expression of NSCLC and to infer clinical outcomes in response to immunotherapy. Additionally, this deep learning model combined with clinical models demonstrated improved stratification capabilities.
Topics & Concepts
MedicineHazard ratioLung cancerInternal medicineImmunotherapyCohortOncologyConfidence intervalMalignancyReceiver operating characteristicCancerPD-L1Proportional hazards modelCancer Immunotherapy and BiomarkersRadiomics and Machine Learning in Medical ImagingLung Cancer Diagnosis and Treatment