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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

  
@article{QIMS117947,
	author = {Rong Zhang and Minping Hong and Hongjie Cai and Yanting Liang and Xinjie Chen and Ziwei Liu and Meilian Wu and Cuiru Zhou and Chenzhengren Bao and Huafeng Wang and Shaomin Yang and Qiugen Hu},
	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},
	keywords = {},
	abstract = {},
	issn = {2223-4306},	url = {https://qims.amegroups.org/article/view/117947}
}