Dynamic recurrent neural networks for a hybrid intelligent decision support system for the metallurgical industry. - Shang-Ming Zhou; Li Da Xu (Expert Syst. J. Knowl. Eng., 1999)

A new type of recurrent fuzzy neural network for modeling dynamic systems. - Shang-Ming Zhou; Li Da Xu (Knowl. Based Syst., 2001)

A variational approach to intensity approximation for remote sensing images using dynamic neural networks. - Shang-Ming Zhou; Hong-Xing Li 004; Lida Xu (Expert Syst. J. Knowl. Eng., 2003)

Interpretability improvement of input space partitioning by merging fuzzy sets based on an entropy measure. - Shang-Ming Zhou; John Q. Gan (FUZZ-IEEE, 2004)

Mercer Kernel, Fuzzy C-Means Algorithm, and Prototypes of Clusters. - Shang-Ming Zhou; John Q. Gan (IDEAL, 2004)

Improving the interpretability of Takagi-Sugeno fuzzy model by using linguistic modifiers and a multiple objective learning scheme. - Shang-Ming Zhou; John Q. Gan (IJCNN, 2004)

An Unsupervised Kernel Based Fuzzy C-Means Clustering Algorithm With Kernel Normalisation. - Shang-Ming Zhou; John Q. Gan (Int. J. Comput. Intell. Appl., 2004)

A New Fuzzy Membership Function with Applications in Interpretability Improvement of Neurofuzzy Models. - John Q. Gan; Shang-Ming Zhou (ICIC (2), 2006)

Constructing accurate and parsimonious fuzzy models with distinguishable fuzzy sets based on an entropy measure. - Shang-Ming Zhou; John Q. Gan (Fuzzy Sets Syst., 2006)

A new fuzzy relaxation algorithm for image enhancement. - Shang-Ming Zhou; John Q. Gan (Int. J. Knowl. Based Intell. Eng. Syst., 2006)

Machine learning and intelligent data analysis for interpretable neuro-fuzzy system modelling. - Shang-Ming Zhou (2006)

Multiple Objective Learning for Constructing Interpretable Takagi-Sugeno Fuzzy Model. - Shang-Ming Zhou; John Q. Gan (Multi-Objective Machine Learning, 2006)

A Novel Approach to Type-2 Fuzzy Addition. - William Blewitt; Shang-Ming Zhou; Simon Coupland (FUZZ-IEEE, 2007)

New Type-2 Rule Ranking Indices for Designing Parsimonious Interval Type-2 Fuzzy Logic Systems. - Shang-Ming Zhou; Robert I. John; Francisco Chiclana; Jonathan M. Garibaldi (FUZZ-IEEE, 2007)

Interactive image enhancement by fuzzy relaxation. - Shang-Ming Zhou; John Q. Gan; Lida Xu; Robert I. John (Int. J. Autom. Comput., 2007)

Constructing L2-SVM-Based Fuzzy Classifiers in High-Dimensional Space With Automatic Model Selection and Fuzzy Rule Ranking. - Shang-Ming Zhou; John Q. Gan (IEEE Trans. Fuzzy Syst., 2007)

Compact fuzzy rules induction and feature extraction using SVM with particle swarms for breast cancer treatments. - Shang-Ming Zhou; Robert Ivor John; Xiao-Ying Wang; Jonathan M. Garibaldi; Ian O. Ellis (IEEE Congress on Evolutionary Computation, 2008)

Inducing linguistic weights for type-1 OWA operators in soft decision making. - Shang-Ming Zhou; Francisco Chiclana (FUZZ-IEEE, 2008)

Type-2 OWA operators - aggregating type-2 fuzzy sets in soft decision making. - Shang-Ming Zhou; Francisco Chiclana; Robert Ivor John; Jonathan M. Garibaldi (FUZZ-IEEE, 2008)

Surface Reconstruction Techniques Using Neural Networks to Recover Noisy 3D Scenes. - David A. Elizondo; Shang-Ming Zhou; Charalambos Chrysostomou (ICANN (1), 2008)

Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers. - Shang-Ming Zhou; Francisco Chiclana; Robert Ivor John; Jonathan M. Garibaldi (Fuzzy Sets Syst., 2008)

Low-level interpretability and high-level interpretability: a unified view of data-driven interpretable fuzzy system modelling. - Shang-Ming Zhou; John Q. Gan (Fuzzy Sets Syst., 2008)

Classifying mental tasks based on features of higher-order statistics from EEG signals in brain-computer interface. - Shang-Ming Zhou; John Q. Gan; Francisco Sepulveda (Inf. Sci., 2008)

Methods of interpretation of a non-stationary fuzzy system for the treatment of breast cancer. - Xiao-Ying Wang; Jonathan M. Garibaldi; Shang-Ming Zhou; Robert Ivor John (FUZZ-IEEE, 2009)

Type-1 OWA operator based non-stationary fuzzy decision support systems for breast cancer treatments. - Shang-Ming Zhou; Jonathan M. Garibaldi; Francisco Chiclana; Robert Ivor John; Xiao-Ying Wang (FUZZ-IEEE, 2009)

Fuzziness index driven fuzzy relaxation algorithm and applications to image processing. - Shang-Ming Zhou; John Q. Gan; Lida Xu; Robert Ivor John (Ann. Oper. Res., 2009)

On Constructing Parsimonious Type-2 Fuzzy Logic Systems via Influential Rule Selection. - Shang-Ming Zhou; Jonathan M. Garibaldi; Robert Ivor John; Francisco Chiclana (IEEE Trans. Fuzzy Syst., 2009)

Extracting Takagi-Sugeno Fuzzy Rules with Interpretable Submodels via Regularization of Linguistic Modifiers. - Shang-Ming Zhou; John Q. Gan (IEEE Trans. Knowl. Data Eng., 2009)

Construction of parsimonious Takagi-Sugeno fuzzy rule based model in characterising impacts of child health, socioeconomic deprivations on educational outcomes. - Shang-Ming Zhou; Ronan A. Lyons; Mike B. Gravenor (FUZZ-IEEE, 2010)

SVM with entropy regularization and particle swarm optimization for identifying children's health and socioeconomic determinants of education attainments using linked datasets. - Shang-Ming Zhou; Ronan A. Lyons; Owen Bodger; Joanne C. Demmler; Mark D. Atkinson (IJCNN, 2010)

A novel Bayesian learning method for information aggregation in modular neural networks. - Pan Wang 009; Lida Xu; Shang-Ming Zhou; Zhun Fan; Youfeng Li; Shan Feng (Expert Syst. Appl., 2010)

On aggregating uncertain information by type-2 OWA operators for soft decision making. - Shang-Ming Zhou; Robert Ivor John; Francisco Chiclana; Jonathan M. Garibaldi (Int. J. Intell. Syst., 2010)

The Type-1 OWA Operator and the Centroid of Type-2 Fuzzy Sets. - Francisco Chiclana; Shang-Ming Zhou (EUSFLAT Conf., 2011)

Alpha-Level Aggregation: A Practical Approach to Type-1 OWA Operation for Aggregating Uncertain Information with Applications to Breast Cancer Treatments. - Shang-Ming Zhou; Francisco Chiclana; Robert Ivor John; Jonathan M. Garibaldi (IEEE Trans. Knowl. Data Eng., 2011)

Fuzzification of the OWA Operators for Aggregating Uncertain Information with Uncertain Weights. - Shang-Ming Zhou; Francisco Chiclana; Robert Ivor John; Jonathan M. Garibaldi (Recent Developments in the Ordered Weighted Averaging Operators, 2011)

Incorporation of expert variability into breast cancer treatment recommendation in designing clinical protocol guided fuzzy rule system models. - Jonathan M. Garibaldi; Shang-Ming Zhou; Xiao-Ying Wang; Robert Ivor John; Ian O. Ellis (J. Biomed. Informatics, 2012)

Guest Editorial Special Section on Enterprise Systems. - Zu De Zhou; Ricardo Valerdi; Shang-Ming Zhou (IEEE Trans. Ind. Informatics, 2012)

Guest EditorialIntegrated Healthcare Information Systems. - Ling Li 008; Ri-Li Ge; Shang-Ming Zhou; Ricardo Valerdi (IEEE Trans. Inf. Technol. Biomed., 2012)

Type-Reduction of General Type-2 Fuzzy Sets: The Type-1 OWA Approach. - Francisco Chiclana; Shang-Ming Zhou (Int. J. Intell. Syst., 2013)

Conversational Interaction Recognition Based on Bodily and Facial Movement. - Jingjing Deng 001; Xianghua Xie; Shang-Ming Zhou (ICIAR (1), 2014)

Using EEG artifacts for BCI applications. - Wanli Ma; Dat Tran 001; Trung Le 001; Hong Lin; Shang-Ming Zhou (IJCNN, 2014)

Mining textual data from primary healthcare records: Automatic identification of patient phenotype cohorts. - Shang-Ming Zhou; Muhammad A. Rahman; Mark D. Atkinson; Sinead Brophy (IJCNN, 2014)

Type-1 OWA methodology to consensus reaching processes in multi-granular linguistic contexts. - Francisco Mata; Luis G. Pérez; Shang-Ming Zhou; Francisco Chiclana (Knowl. Based Syst., 2014)

Guest Editorial Special Section on IoT. - Zu De Zhou; Ricardo Valerdi; Shang-Ming Zhou; Li Wang (IEEE Trans. Ind. Informatics, 2014)

Introduction: Advances in IoT research and applications. - Pan Wang 009; Ricardo Valerdi; Shang-Ming Zhou; Ling Li 008 (Inf. Syst. Frontiers, 2015)

Light source detection for digital images in noisy scenes: a neural network approach. - David A. Elizondo; Shang-Ming Zhou; Charalambos Chrysostomou (Neural Comput. Appl., 2017)

Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface. - Haider Raza; Dheeraj Rathee; Shang-Ming Zhou; Hubert Cecotti; Girijesh Prasad (Neurocomputing, 2019)

A Comparison of Explanations Given by Explainable Artificial Intelligence Methods on Analysing Electronic Health Records. - Jamie Andrew Duell; Xiuyi Fan; Bruce Burnett; Gert Aarts; Shang-Ming Zhou (BHI, 2021)

ExMed: An AI Tool for Experimenting Explainable AI Techniques on Medical Data Analytics. - Marcin Kapcia; Hassan Eshkiki; Jamie Andrew Duell; Xiuyi Fan; Shang-Ming Zhou; Benjamin Mora (ICTAI, 2021)

Towards a Shapley Value Graph Framework for Medical peer-influence. - Jamie Andrew Duell; Monika Seisenberger; Gert Aarts; Shang-Ming Zhou; Xiuyi Fan (CoRR, 2021)

Type-1 OWA Operators in Aggregating Multiple Sources of Uncertain Information: Properties and Real-World Applications in Integrated Diagnosis. - Shang-Ming Zhou; Francisco Chiclana; Robert I. John; Jonathan M. Garibaldi; Lin Huo (IEEE Trans. Fuzzy Syst., 2021)

Automatically Generating Natural Language Descriptions of Images by a Deep Hierarchical Framework. - Lin Huo; Lin Bai; Shang-Ming Zhou (IEEE Trans. Cybern., 2022)

Explainable Artificial Intelligence and Mobile Health for Treating Eating Disorders in Young Adults with Autism Spectrum Disorder Based on the Theory of Change: A Mixed Method Protocol. - Omobolanle Omisade; Alexander E. Gegov; Shang-Ming Zhou; Alice Good; Catherine Tryfona; Sandeep Singh Sengar; Amie-Louise Prior; Bangli Liu; Taiwo Adedeji; Carrie M. Toptan (FICTA (2), 2023)

The role of ontologies and knowledge in Explainable AI. - Roberto Confalonieri 001; Oliver Kutz; Diego Calvanese; Jose Maria Alonso-Moral; Shang-Ming Zhou (Semantic Web, 2024)

Advancing AI Literacy in Medical Education: A Medical AI Competency Framework Development. - Chang Cai; Jamie Andrew Duell; Daisy Minghui Chen; Weng Kin Ho; Bernett Teck Kwong Lee; Fang Li; Siyuan Liu 003; Olivia Ng; Vidya Sudarshan; Shang-Ming Zhou; Gaoxia Zhu; Xiuyi Fan (AIED (5), 2025)

Enhancing Diagnostic Accuracy of Drug-Resistant Tuberculosis on Chest X-Rays Using Data-Efficient Image Transformers. - Joan Jonathan Mnyambo; Amir Aly; Shang-Ming Zhou; Yinghui Wei; Stephen Mullin; Emmanuel C. Ifeachor (BIOSTEC (2): HEALTHINF, 2025)

ieGENES: A machine learning method for selecting differentially expressed genes in cancer studies. - Xiao-Lei Xia; Shang-Ming Zhou; Yunguang Liu; Na Lin; Ian M. Overton (J. Biomed. Informatics, 2025)

AI-driven biomedical perspectives on mental fatigue in the post-COVID-19 Era: trends, research gaps, and future directions. - Saba Parveen; Md Belal Bin Heyat; Umair Tariq; Faijan Akhtar; Hafiz Muhammad Zeeshan; Seth Christopher Yaw Appiah; Shang-Ming Zhou; Huang Lei (J. Big Data, 2025)