Wang Y et al. PATQUANT

This is a dataset of 283 images used for interobserver agreement study in the work: "AI algorithm for lung adenocarcinoma pattern quantification (PATQUANT): International validation and advanced risk stratification superior to conventional grading" by Wang Y. et al. These images were analysed by 13 pathologists and AI tool (PATQUANT). The dataset includes: 1) Images of lung adenocarcinomas (conventional invasive non-mucinous adenocarcinoma, resection cases). 2) CSV files containing all evaluation results: *Raw results with percentages of single pattern for each grader. *Processed results with dominant and secondary pattern / image for each grader. Pattern coding: 1- ACINAR 2- LEPIDIC 3- SOLID 4- MICROPAPILLARY 5- PAPILLARY 6- COMPLEX_GLANDULAR 3) Code used for training, test experiments, and WSI processing. The detailed description of the code components is provided in code_description.txt We do not provide trained checkpoints. More details on composition of dataset, principles of analysis, and other aspects can be found in the publication: [Publication DOI link - appears after publication] This dataset for academic, non-commercial research only. The original publication should be cited in case of using the dataset in further publications.