CT-based artificial intelligence system complementing deep learning model and radiologist for liver fibrosis staging

CT-based artificial intelligence system complementing deep learning model and radiologist for liver fibrosis staging

Summary: Noninvasive methods for liver fibrosis staging are urgently needed due to its significance in predicting significant morbidity and mortality. In this study, we developed an automated DL-based segmentation and classification model (Model-C). Test-time adaptation was used to address data dist...

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Bibliographic Details
Main Authors: Shuang Zheng, Wenao Ma, Lin Mu, Kan He, Jianfeng Cao, Tiffany Y. So, Lei Zhang, Mingyang Li, Yanan Zhai, Feng Liu, Shunlin Guo, Longlin Yin, Liming Zhao, Lei Wang, Heather H.C. Lee, Wei Jiang, Junqi Niu, Pujun Gao, Qi Dou, Huimao Zhang
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:iScience
Subjects:
Public health
Pathophysiology
Artificial intelligence
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004225004857
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