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Development of a deep learning model based on computed tomography automatic segmentation to assist in selecting optimal time-to-surgery and dissected lymph node count for non-small cell lung cancer patients undergoing neoadjuvant immunotherapy and chemotherapy: a multicenter study

   
@article{TLCR113298,
	author = {Junfeng Zhao and Ying Li and Jiaxuan Chen and Chuankun Han and Yifei Yan and Chen Zhou and Yingrui Bai and Yali Xu and Yintao Li},
	title = {Development of a deep learning model based on computed tomography automatic segmentation to assist in selecting optimal time-to-surgery and dissected lymph node count for non-small cell lung cancer patients undergoing neoadjuvant immunotherapy and chemotherapy: a multicenter study},
	journal = {Translational Lung Cancer Research},
	volume = {15},
	number = {3},
	year = {2026},
	keywords = {},
	abstract = {},
	issn = {2226-4477},	url = {https://tlcr.amegroups.org/article/view/113298}
}