A hybrid approach of topic model and matrix factorization based on two-step recommendation framework. - Xiangyu Zhao 004; Zhendong Niu; Wei Chen 042; Chongyang Shi 001; Ke Niu 002; Donglei Liu (J. Intell. Inf. Syst., 2015)

Using CV-CRITIC to Determine Weights for Smart City Evaluation. - Qiaoyun Yin; Ke Niu 002; Ning Li 024 (ICTAI, 2017)

Prediction for Student Academic Performance Using SMNaive Bayes Model. - Baoting Jia; Ke Niu 002; Xia Hou; Ning Li 024; Xueping Peng; Peipei Gu; Ran Jia (ADMA, 2019)

ACO-RR: Ant Colony Optimization Ridge Regression in Reuse of Smart City System. - Qiaoyun Yin; Ke Niu 002; Ning Li 024; Xueping Peng; Yijie Pan (ICSR, 2019)

UTSP: User-Based Two-Step Recommendation With Popularity Normalization Towards Diversity and Novelty. - Ke Niu 002; Xiangyu Zhao 004; Fangfang Li; Ning Li 024; Xueping Peng; Wei Chen 042 (IEEE Access, 2019)

Video highlight extraction via content-aware deep transfer. - Ke Niu 002; Han Wang (Multim. Tools Appl., 2019)

Multichannel Deep Attention Neural Networks for the Classification of Autism Spectrum Disorder Using Neuroimaging and Personal Characteristic Data. - Ke Niu 002; Jiayang Guo; Yijie Pan; Xin Gao 001; Xueping Peng; Ning Li 024; Hailong Li (Complex., 2020)

Readmission Prediction with Knowledge Graph Attention and RNN-Based Ordinary Differential Equations. - Su Pei; Ke Niu 002; Xueping Peng; Jingni Zeng (KSEM, 2021)

Multi-modal Intermediate Fusion Model for diagnosis prediction. - You Lu; Ke Niu 002; Xueping Peng; Jingni Zeng; Su Pei (ICIAI, 2022)

MIFTP: A Multimodal Multi-Level Independent Fusion Framework with Improved Twin Pyramid for Multilabel Chest X-Ray Image Classification. - Jingni Zeng; Ke Niu 002; You Lu; Su Pei; Yuhang Zhou; Zhongmin Guo (ICTAI, 2022)

P-ResUnet: Segmentation of brain tissue with Purified Residual Unet. - Ke Niu 002; Zhongmin Guo; Xueping Peng; Su Pei (Comput. Biol. Medicine, 2022)

A multi-head self-attention deep learning approach for detection and recommendation of neuromagnetic high frequency oscillations in epilepsy. - Xiangyu Zhao 004; Xueping Peng; Ke Niu 002; Hailong Li; Lili He 003; Feng Yang; Ting Wu; Duo Chen; Qiusi Zhang; Menglin Ouyang; Jiayang Guo; Yijie Pan (Frontiers Neuroinformatics, 2022)

Fusion of sequential visits and medical ontology for mortality prediction. - Ke Niu 002; You Lu; Xueping Peng; Jingni Zeng (J. Biomed. Informatics, 2022)

Lightweight Traffic Sign Recognition Model Based on Dynamic Feature Extraction. - Yiyuan Ge; Ke Niu 002; Zhihao Chen; Qinhu Zhang (ICAI (1), 2023)

MedCT-BERT: Multimodal Mortality Prediction using Medical ConvTransformer-BERT Model. - Ke Zhang; Ke Niu 002; Yuhang Zhou; Wenjuan Tai; Guoqiang Lu (ICTAI, 2023)

CGDC- LSTM: A novel hybrid neural network model for MOOC dropout prediction. - Yuhang Zhou; Ke Niu 002; Haoyi Lv; GuoQiang Lu; Yijie Pan (IJCNN, 2023)

A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learning. - Heng Li 010; Haofeng Liu; Huazhu Fu; Yanwu Xu 001; Hui Shu; Ke Niu 002; Yan Hu; Jiang Liu 001 (CoRR, 2023)

A hybrid model for predicting academic performance of engineering undergraduates. - Ke Niu 002; Baoting Jia; Yuhang Zhou; GuoQiang Lu (Int. J. Model. Simul. Sci. Comput., 2023)

Intensive Care Unit readmission prediction with correlation enhanced multi-task learning. - Ke Niu 002; Su Pei; Xueping Peng; Jingni Zeng; Ke Zhang (Comput. Electr. Eng., 2023)

CNN autoencoders and LSTM-based reduced order model for student dropout prediction. - Ke Niu 002; GuoQiang Lu; Xueping Peng; Yuhang Zhou; Jingni Zeng; Ke Zhang (Neural Comput. Appl., 2023)

PMCT: Parallel Multiscale Convolutional Temporal model for MOOC dropout prediction. - Ke Niu 002; Yuhang Zhou; GuoQiang Lu; Wenjuan Tai; Ke Zhang (Comput. Electr. Eng., 2023)

A generic fundus image enhancement network boosted by frequency self-supervised representation learning. - Heng Li 010; Haofeng Liu; Huazhu Fu; Yanwu Xu 001; Hai Shu; Ke Niu 002; Yan Hu; Jiang Liu 001 (Medical Image Anal., 2023)

PESAM: Privacy-Enhanced Segment Anything Model for Medical Image Segmentation. - Jiuyun Cai; Ke Niu 002; Yijie Pan; Wenjuan Tai; Jiacheng Han (ICIC (2), 2024)

Self-KT: Self-attentive Knowledge Tracing with Feature Fusion Pre-training in Online Education. - Guoqiang Lu; Ke Niu 002; Xueping Peng; Yuhang Zhou; Ke Zhang; Wenjuan Tai (IJCNN, 2024)

Enhancing and Adapting in the Clinic: Source-Free Unsupervised Domain Adaptation for Medical Image Enhancement. - Heng Li 010; Ziqin Lin; Zhongxi Qiu; Zinan Li; Ke Niu 002; Na Guo; Huazhu Fu; Yan Hu; Jiang Liu 001 (IEEE Trans. Medical Imaging, 2024)

AIF-SFDA: Autonomous Information Filter Driven Source-Free Domain Adaptation for Medical Image Segmentation. - Haojin Li; Heng Li 010; Jianyu Chen; Rihan Zhong; Ke Niu 002; Huazhu Fu; Jiang Liu 001 (AAAI, 2025)

MedMaskDiff: Mamba-Based Medical Semantic Image Synthesis for Segmentation. - Jiacheng Han; Ke Niu 002; Jiuyun Cai (ICIC (26), 2025)

PedFed: A performance evaluation-driven federated learning framework for efficient communication. - Ke Niu 002; Wenjuan Tai; Xueping Peng; Zhongmin Guo; Can Zhang; Heng Li 010 (Int. J. Model. Simul. Sci. Comput., 2025)

Multi-View Test-Time Adaptation for Semantic Segmentation in Clinical Cataract Surgery. - Heng Li 010; Mingyang Ou; Haojin Li; Zhongxi Qiu; Ke Niu 002; Huazhu Fu; Jiang Liu 001 (IEEE Trans. Medical Imaging, 2025)

Endoscopic Depth Estimation Based on Deep Learning: A Survey. - Ke Niu 002; Zeyun Liu; Xue Feng; Heng Li 010; Kaize Shi (CoRR, 2025)

SAFedHDM: Semi-asynchronous federated learning with highlight diffusion model for medical image segmentation. - Ke Niu 002; Jiuyun Cai; Xue Feng (Inf. Fusion, 2026)