# NSCLC Subtyping in Conventional Cytology: Results of the International Association for the Study of Lung Cancer Cytology Working Group Survey to Determine Specific Cytomorphologic Criteria for Adenocarcinoma and Squamous Cell Carcinoma

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/nsclc-subtyping-in-conventional-cytology-results-of-the-international/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Deepali Jain,Aruna Nambirajan,Gang Chen,Kim R. Geisinger,Kenzo Hiroshima,Lester J. Layfield,Yuko Minami,André L. Moreira,Noriko Motoi,Mauro Papotti,Natasha Rekhtman,Prudence A. Russell,Spasenija Savic Prince,Fernando Schmitt,Yasushi Yatabe,Serenella Eppenberger‐Castori,Lukas Bubendorf,Mary Beth Beasley,Sabina Berezowska,Alain Borczuk,E. Brambilla,Teh‐Ying Chou,Jin-Haeng Chung,Wendy A. Cooper,Sanja Đačić,Yuchen Chan,Fred R. Hirsch,David Hwang,Philippe Joubert,Keith M. Kerr,Sylvie Lantuéjoul,Dongmei Lin,Fernando López‐Ríos,Daisuke Matsubara,Mari Mino–Kenudson,Andrew G. Nicholson,Claudia Poleri,Anja C. Roden,Kurt A. Schalper,Lynette M. Sholl,Erik Thunnissen,William D. Travis,Ming‐Sound Tsao,Ignacio I. Wistuba,Gang Chen |
| Citations | 35 |
| DOI | 10.1016/j.jtho.2022.02.013 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | bronze |
| OA URL | http://www.jto.org/article/S1556086422001459/pdf |
| OpenAlex ID | https://openalex.org/W4220659516 |
| PMID | 35331963 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Aruna Nambirajan](https://scholariq.org/researchers/aruna-nambirajan/)

## Paper journal

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

## Paper primary topic

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Paper topics

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

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