# Radiomics Study for Predicting the Expression of PD-L1 and Tumor Mutation Burden in Non-Small Cell Lung Cancer Based on CT Images and Clinicopathological Features

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/radiomics-study-for-predicting-the-expression-of-pd-l1-and-tumor-mutation-burden/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Qiang Wen,Zhe Yang,Honghai Dai,Alei Feng,Qiang Li |
| Citations | 79 |
| DOI | 10.3389/fonc.2021.620246 |
| Fields | Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.frontiersin.org/articles/10.3389/fonc.2021.620246/pdf |
| OpenAlex ID | https://openalex.org/W3190850324 |
| PMID | 34422625 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Qiang Li](https://scholariq.org/researchers/qiang-li/)

## Paper journal

- [Frontiers in Oncology](https://scholariq.org/journals/frontiers-in-oncology/)

## Paper primary topic

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)

## Paper topics

- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Cancer Immunotherapy and Biomarkers](https://scholariq.org/topics/cancer-immunotherapy-and-biomarkers/)
- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.