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Predicting the pathological invasiveness in patients with a solitary pulmonary nodule via Shapley additive explanations interpretation of a tree-based machine learning radiomics model: a multicenter study
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@article{{QIMS}{117947}, author = {Zhang, R., Hong, M., Cai, H., Liang, Y., Chen, X., Liu, Z., Wu, M., Zhou, C., Bao, C., Wang, H., Yang, S., Hu, Q.}, title = {Predicting the pathological invasiveness in patients with a solitary pulmonary nodule via Shapley additive explanations interpretation of a tree-based machine learning radiomics model: a multicenter study}, journal = {Quantitative Imaging in Medicine and Surgery}, volume = {13}, number = {12}, year = {2023}, url = {https://qims.amegroups.org/article/view/117947} }