Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses

Artificial intelligence links CT images to pathologic features and survival outcomes of renal masses

Abstract Treatment decisions for an incidental renal mass are mostly made with pathologic uncertainty. Improving the diagnosis of benign renal masses and distinguishing aggressive cancers from indolent ones is key to better treatment selection. We analyze 13261 pre-operative computed computed tomogr...

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Main Authors: Ying Xiong, Linpeng Yao, Jinglai Lin, Jiaxi Yao, Qi Bai, Yuan Huang, Xue Zhang, Risheng Huang, Run Wang, Kang Wang, Yu Qi, Pingyi Zhu, Haoran Wang, Li Liu, Jianjun Zhou, Jianming Guo, Feng Chen, Chenchen Dai, Shuo Wang
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-56784-z
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https://doi.org/10.1038/s41467-025-56784-z

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