Deep Learning Predicts <i>EGFR</i> Mutation Status from Histology Images in Non–Small Cell Lung Cancer
DL predicts EGFR mutations in NSCLC from routine histology images, achieving an overall AUROC of 0.905 and 0.860 in two independent test sets across histologic subtypes, mutation subtypes, and imaging platforms.
Authors
- Jin-Haeng Chung (ORCID: https://orcid.org/0000-0002-6527-3814)
- Yoon‐La Choi (ORCID: https://orcid.org/0000-0002-5788-5140)
- Woochan Hwang (ORCID: https://orcid.org/0000-0002-9874-7772)
- Taebum Lee (ORCID: https://orcid.org/0000-0002-9472-0644)
- L. Henry Moore (ORCID: https://orcid.org/0009-0009-4534-4716)
- H. M. Bannister (ORCID: https://orcid.org/0009-0007-8074-0736)
- James B. Rawson (ORCID: https://orcid.org/0009-0000-1313-6159)
- Seokhwi Kim (ORCID: https://orcid.org/0000-0001-7646-5064)
- Chang Ho Ahn (ORCID: https://orcid.org/0000-0002-0702-0608)
- Chan‐Young Ock (ORCID: https://orcid.org/0000-0002-6755-9728)
- Sérgio Pereira (ORCID: https://orcid.org/0000-0002-4298-0903)
- Se‐Hoon Lee (ORCID: https://orcid.org/0000-0002-9219-3350)
- Michael J.T. Senior (ORCID: https://orcid.org/0000-0002-9064-7769)
- Sangwon Shin (ORCID: https://orcid.org/0009-0003-2626-3052)
- Biagio Brattoli (ORCID: https://orcid.org/0000-0002-8482-3375)
- Siraj M. Ali (ORCID: https://orcid.org/0000-0001-7477-4023)
- Talha Qaiser (ORCID: https://orcid.org/0000-0002-5014-7399)
- Hyojin Kim (ORCID: https://orcid.org/0000-0001-9201-8328)
- Jongchan Park (ORCID: https://orcid.org/0000-0001-9808-6823)
- Ross J. Hill (ORCID: https://orcid.org/0000-0003-2847-6855)
- Elia Riboni-Verri (ORCID: https://orcid.org/0009-0005-6999-5792)
- Seongho Keum (ORCID: https://orcid.org/0009-0008-0954-9389)
Institutions
- AstraZeneca (United Kingdom) (GB)
- University of Seoul (KR)
- Samsung Medical Center (KR)
- Seoul National University Bundang Hospital (KR)
- Abzena (United Kingdom) (GB)
- Lutronic (South Korea) (KR)
- Lukenya University (KE)
- Ajou University (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Cancer Research Communications
- Published
- 2025-11-10
- DOI
- https://doi.org/10.1158/2767-9764.crc-25-0155
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- AstraZeneca
- Illinois Nutrient Research and Education Council