RDNet: ResNet-18 with Dropout for Blood Cell Classification. - Ziquan Zhu; Zeyu Ren; Shui-Hua Wang; Juan Manuel Górriz; Yudong Zhang 001 (IWINAC (1), 2022)

NAGNN: Classification of COVID-19 based on neighboring aware representation from deep graph neural network. - Siyuan Lu 001; Ziquan Zhu; Juan Manuel Górriz; Shui-Hua Wang; Yu-Dong Zhang 001 (Int. J. Intell. Syst., 2022)

ODET: Optimized Deep ELM-based Transfer Learning for Breast Cancer Explainable Detection. - Ziquan Zhu; Shuihua Wang (EAI Endorsed Trans. Scalable Inf. Syst., 2022)

DLBCNet: A Deep Learning Network for Classifying Blood Cells. - Ziquan Zhu; Zeyu Ren; Siyuan Lu 001; Shuihua Wang; Yudong Zhang 001 (Big Data Cogn. Comput., 2023)

TBDLNet: a network for classifying multidrug-resistant and drug-sensitive tuberculosis. - Ziquan Zhu; Jing Tao; Shuihua Wang; Xin Zhang 071; Yudong Zhang 001 (CoRR, 2023)

WACPN: A Neural Network for Pneumonia Diagnosis. - Shui-Hua Wang; Muhammad Attique Khan; Ziquan Zhu; Yudong Zhang 001 (Comput. Syst. Sci. Eng., 2023)

SNELM: SqueezeNet-Guided ELM for COVID-19 Recognition. - Yudong Zhang 001; Muhammad Attique Khan; Ziquan Zhu; Shuihua Wang (Comput. Syst. Sci. Eng., 2023)

Deep learning in food category recognition. - Yudong Zhang 001; Lijia Deng; Hengde Zhu; Wei Wang 357; Zeyu Ren; Qinghua Zhou; Siyuan Lu 001; Shiting Sun; Ziquan Zhu; Juan Manuel Górriz; Shuihua Wang (Inf. Fusion, 2023)

AdaD-FNN for Chest CT-Based COVID-19 Diagnosis. - Xujing Yao; Ziquan Zhu; Cheng Kang; Shui-Hua Wang; Juan Manuel Górriz; Yu-Dong Zhang 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2023)

CovC-ReDRNet: A Deep Learning Model for COVID-19 Classification. - Hanruo Zhu; Ziquan Zhu; Shuihua Wang; Yu-Dong Zhang 001 (Mach. Learn. Knowl. Extr., 2023)

FECNet: a Neural Network and a Mobile App for COVID-19 Recognition. - Yudong Zhang 001; Vishnuvarthanan Govindaraj; Ziquan Zhu (Mob. Networks Appl., 2023)

Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends. - J. M. Górriz; I. Álvarez Illán; Agustín Álvarez-Marquina; Juan Eloy Arco; Martin Atzmüller; F. Ballarini; Emilia I. Barakova; Guido Bologna; María Paula Bonomini; Germán Castellanos-Domínguez; Diego Castillo-Barnes; S. B. Cho; et al. (Inf. Fusion, 2023)

Rethinking Personalized Federated Learning from Knowledge Perspective. - Dezhong Yao 002; Ziquan Zhu; Tongtong Liu 006; Zhiqiang Xu 003; Hai Jin 001 (ICPP, 2024)

OPT-CO: Optimizing pre-trained transformer models for efficient COVID-19 classification with stochastic configuration networks. - Ziquan Zhu; Lu Liu 001; Robert C. Free; Ashiq Anjum; John Panneerselvam (Inf. Sci., 2024)

SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training. - Tianjin Huang; Ziquan Zhu; Gaojie Jin; Lu Liu; Zhangyang Wang; Shiwei Liu 003 (ICLR, 2025)

CTBViT: A novel ViT for tuberculosis classification with efficient block and randomized classifier. - Si-Yuan Lu; Ziquan Zhu; Yao Tang; Xin Zhang; Xingxiang Liu (Biomed. Signal Process. Control., 2025)

Tuberculosis and pneumonia diagnosis in chest X-rays by large adaptive filter and aligning normalized network with report-guided multi-level alignment. - Si-Yuan Lu 001; Ziquan Zhu; Yu-Dong Zhang; Yu-Dong Yao (Eng. Appl. Artif. Intell., 2025)