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National Science Review|June 27, 2024
Deep carbon recycling viewed from global plate tectonicsMaoliang Zhang, Sheng Xu, Yuji Sano
Frontiers in Oncology|September 24, 2025
Evaluation of a PSA and transrectal prostate ultrasound video-based machine learning model as a tool for prostate cancer diagnosisYanhong Du, Anli Zhao, Maoliang Zhang, et al.
Materials (Basel, Switzerland)|August 14, 2025
Fracture Behavior of Steel-Fiber-Reinforced High-Strength Self-Compacting Concrete: A Digital Image Correlation AnalysisMaoliang Zhang, Junpeng Chen, Junxia Liu, et al.
Annali Italiani Di Chirurgia|January 15, 2026
Development and Validation of a Machine Learning-Based Radiomics Model Using Ultrasound Image Features for Prostate Cancer Risk StratificationAnli Zhao, Shunlan Du, Yanhong Du, et al.
Materials (Basel, Switzerland)|November 13, 2025
Effect of Na<sub>2</sub>O, MgO, CaO, and Fe<sub>2</sub>O<sub>3</sub> on Characteristics of Ceramsite Prepared from Lead-Zinc Tailings and Coal GangueZhongtao Luo, Qi Zhang, Jinyang Guo, et al.
Frontiers in Oncology|September 12, 2022
Machine learning prediction of prostate cancer from transrectal ultrasound video clipsKai Wang, Peizhe Chen, Bojian Feng, et al.
Frontiers in Endocrinology|March 27, 2023
Value of machine learning-based transrectal multimodal ultrasound combined with PSA-related indicators in the diagnosis of clinically significant prostate cancerMaoliang Zhang, Yuanzhen Liu, Jincao Yao, et al.
Frontiers in Oncology|June 1, 2023
Comparison of machine learning models based on multi-parametric magnetic resonance imaging and ultrasound videos for the prediction of prostate cancerXiaoyang Qi, Kai Wang, Bojian Feng, et al.
European Journal of Radiology|August 18, 2023
The auxiliary diagnosis of thyroid echogenic foci based on a deep learning segmentation model: A two-center studyYuanzhen Liu, Chen Chen, Kai Wang, et al.
BMC Cancer|November 23, 2023
Deep learning approaches for differentiating thyroid nodules with calcification: a two-center studyChen Chen, Yuanzhen Liu, Jincao Yao, et al.
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