# Clinicopathologic and Genotypic Features of Lung Adenocarcinoma Characterized by the International Association for the Study of Lung Cancer Grading System

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/clinicopathologic-and-genotypic-features-of-lung-adenocarcinoma-characterized-by/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Ryo Fujikawa,Yuji Muraoka,Jumpei Kashima,Yukihiro Yoshida,Kimiteru Ito,Hirokazu Watanabe,Masahiko Kusumoto,Shun‐ichi Watanabe,Yasushi Yatabe |
| Citations | 115 |
| DOI | 10.1016/j.jtho.2022.02.005 |
| Fields | Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | http://www.jto.org/article/S1556086422000958/pdf |
| OpenAlex ID | https://openalex.org/W4214721783 |
| PMID | 35227909 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Jumpei Kashima](https://scholariq.org/researchers/jumpei-kashima/)

## Paper journal

- [Journal of Thoracic Oncology](https://scholariq.org/journals/journal-of-thoracic-oncology/)

## Paper primary topic

- [Lung Cancer Diagnosis and Treatment](https://scholariq.org/topics/lung-cancer-diagnosis-and-treatment/)

## Paper topics

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

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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.