Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning. - Ziyi Liu 003; Sijie Ni; Chunmei Yang; Weihao Sun; Deqing Huang; Hu Su; Jian Shu; Na Qin (Comput. Biol. Medicine, 2021)

Efficient Axillary Lymph Node Detection Via Two-stage Spatial-information-fusion-based CNN. - Ziyi Liu 003; Deqing Huang; Chunmei Yang; Jian Shu; Jinhan Li; Na Qin (Comput. Methods Programs Biomed., 2022)

High-Accuracy and Adaptive Fault Diagnosis of High-Speed Train Bogie Using Dense-Squeeze Network. - Yiming Zhang 021; Na Qin; Deqing Huang; Bi Wu; Ziyi Liu 003 (IEEE Trans. Veh. Technol., 2022)

Enhancing Robustness in Multi-modal CT Image Segmentation with a Clustering-based Deep Active Learning Approach. - Aisen Yang; Lulu Xu; Ziyi Liu 003; Na Qin; Deqing Huang (SAFEPROCESS, 2023)

Prediction of esophageal and gastric varices rebleeding for cirrhotic patients based on deep learning. - Ziyi Liu 003; Lulu Xu; Na Qin; Aisen Yang; Yuan Chen; Deqing Huang; Jian Shu (Biomed. Signal Process. Control., 2023)

ITFD: an instance-level triplet few-shot detection network under weighted pair-resampling. - Xin Chen; Chaoyong Peng; Chunrong Qiu; Lin Luo 001; Deqing Huang; Ziyi Liu 003 (Appl. Intell., 2023)

MFU-Net: a deep multimodal fusion network for breast cancer segmentation with dual-layer spectral detector CT. - Aisen Yang; Lulu Xu; Na Qin; Deqing Huang; Ziyi Liu 003; Jian Shu (Appl. Intell., 2024)