Machine learning‐based gene alteration prediction model for primary lung cancer using cytologic images-Reference-Cited by-同舟云学术

Machine learning‐based gene alteration prediction model for primary lung cancer using cytologic images

Published:2022-06-20 Issue:10 Volume:130 Page:812-823
ISSN:1934-662X
Container-title:Cancer Cytopathology
language:en
Short-container-title:Cancer Cytopathology

Author:

Ishii Shuhei¹²^ORCID,Takamatsu Manabu¹³,Ninomiya Hironori¹³,Inamura Kentaro¹³,Horai Takeshi⁴⁵,Iyoda Akira⁶,Honma Naoko⁷,Hoshi Rira¹,Sugiyama Yuko⁵,Yanagitani Noriko⁴⁵,Mun Mingyon⁸,Abe Hitoshi⁵,Mikami Tetuo⁷,Takeuchi Kengo¹³⁹

Affiliation:

1. Department of Pathology Cancer Institute Hospital, Japanese Foundation for Cancer Research Tokyo Japan

2. Department of Pathology Toho University Graduate School of Medicine Tokyo Japan

3. Division of Pathology Cancer Institute, Japanese Foundation for Cancer Research Tokyo Japan

4. Department of Thoracic Medical Oncology Cancer Institute Hospital, Japanese Foundation for Cancer Research Tokyo Japan

5. Department of Cytology Cancer Institute Hospital, Japanese Foundation for Cancer Research Tokyo Japan

6. Division of Chest Surgery, Department of Surgery Toho University School of Medicine Tokyo Japan

7. Department of Pathology Toho University School of Medicine Tokyo Japan

8. Department of Thoracic Surgical Oncology Cancer Institute Hospital, Japanese Foundation for Cancer Research Tokyo Japan

9. Pathology Project for Molecular Targets Cancer Institute, Japanese Foundation for Cancer Research Tokyo Japan

Funder

Japan Society for the Promotion of Science

Publisher

Wiley

Subject

Cancer Research,Oncology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cncy.22609

Reference31 articles.

1. The 2021 WHO Classification of Lung Tumors: Impact of advances since 2015

2. Molecular profile of KRAS G12C-mutant colorectal and non-small-cell lung cancer

3. The CLIP1–LTK fusion is an oncogenic driver in non‐small‐cell lung cancer

4. Identification of Factors Affecting the Success of Next-Generation Sequencing Testing in Solid Tumors

5. The estimation of tumor cell percentage for molecular testing by pathologists is not accurate

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Molekulare Zytologie: Chancen und Herausforderungen;Die Pathologie;2022-12