Abstract
Effective diagnosis and treatment of lung adenocarcinoma depends on accurate typing, subtyping, and grading. Herein, we present the CLWD dataset, a valuable resource for the lung cancer pathology community, comprising 408 whole-slide images (WSIs) from 210 patients specifically curated for the study of lung adenocarcinoma subtypes. Scanned at 80 × magnification, it is one of the largest datasets in Asia, with a particular emphasis on Chinese patient demographics. Notably, the dataset includes comprehensive clinical information, such as age, sex, and diagnosis, providing a robust foundation for diverse research needs. Publicly accessible, it supports a range of applications, including machine learning model development and validation. An initial evaluation of lung adenocarcinoma subtype classification using a multi-instance learning framework demonstrated that this dataset can substantially advance global research and improve the accuracy of subtype diagnosis.
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Data availability
The dataset is publicly available via Figshare24 and can also be accessed directly through our Pathology Image Repository (https://leelab.kmmu.edu.cn/PathologyRepository). Otherwise, the JPG version of the dataset also available at the Hugging Face repository (https://huggingface.co/datasets/kmmuleelab/Lung_Pathology_Image_JPG).
Code availability
The code for preprocessing and deep learning models is publicly available on GitHub: https://github.com/DrNeilChen/CLWD.
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Acknowledgements
This study was supported by the National Natural Science Foundation of China (No. 82560572, No. 82404091, and No. 62302429), the Yunnan Province Applied Basic Research Program Kunming Medical University Joint Project (202401AY070001-120), the Health Commission Foundation of Yunnan Province (2023-KHRCBZ-B15), the Kunming University of Science and Technology Joint Medical Project (KUST-KH2023013Y), Yunnan Fundamental Research Projects(202501CF070023), Kunming University of Science and Technology Joint Medical Project (KUST-KH2022018Y), Major Science and Technology Projects of Yunnan Province (202402AA310016), Basic Research Science and Technology Foundation of Yunnan Province (202201AS070009) and Xing Dian Foundation of Yunnan Province (XDYC-MY-2022-0029).
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Conceptualization: J.P., J.L., D.P.T. and J.N.; Methodology and formal analysis: Y.C., H.Y.Z. and J.L.; Investigation: Y.C., H.Y.Z. and L.W.; Data curation: L.W., L.L., R.S.L., Y.H.J., P.R.T. and Y.L.; Writing-Original Draft: Y.C. and H.Y.Z.; Writing-Review & Editing: L.L., J.P., J.L., D.P.T. and J.N.; Supervision: J.P., J.L., D.P.T. and J.N. All authors have read and approved the final manuscript.
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Chen, Y., Zhao, H., Wang, L. et al. CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification. Sci Data (2026). https://doi.org/10.1038/s41597-026-06906-z
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DOI: https://doi.org/10.1038/s41597-026-06906-z
