Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer

An Integration of a Computed Tomography/Positron Emission Tomography/Whole Slide Image (CT/PET/WSI) Based Deep Learning Signature for Predicting Complete Pathological Response to Neoadjuvant Chemoimmunotherapy in Non-small Cell Lung Cancer: A Multicenter Study

The purpose of this study is to evaluate the performance of a CT/PET/ WSI-based deep learning signature for predicting complete pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer

Inclusion Criteria:

1. Age ranging from 20-75 years;
2. Patients who underwent curative surgery after neoadjuvant chemoimmunotherapy for NSCLC;
3. Obtained written informed consent.

Exclusion Criteria:

1. Missing image data;
2. Pathological N3 disease.