# Authors Title Details Date Pdf/Links/Bibtex Keywords
26Yapicioglu F.R., Rigenti A., Cisci A., Aksoy M., Vitali F., Longo L.Residual Value Prediction in Automotive: A Review of Methods and Data with Research Roadmap IEEE Access 2026 Residual Value Prediction • Artificial Intelligence • Explainability • Uncertainty Quantification
25 Nakanishi T. Longo L.Approximate-Inverse Explainability of beta–VAE Latents for Multichannel EEG Participant-generalised Topographical Representation Learning IEEE Access 2025 Electroencephalography • Brain modeling • Spatial coherence • Scalp • Perturbation methods • Computational modeling • Explainable AI • Deep learning • Electroencephalography • VAE • topographic mapping • approximate inverse model explanations • generative deep learning • representation learning
10.1109/ACCESS.2025.3635543
24Ephrem Tibebe Mekonnen; Longo L., Dondio P.LOMATCE: LOcal Model-Agnostic Time-series Classification Explanations IEEE Access 2025 Time series analysis • Adaptation models • Explainable AI • Predictive models • Data models • Closed box • Perturbation methods • Computational modeling • Deep learning • Kernel • Explainable Artificial Intelligence • Model-agnostic • Time series • Post hoc • Deep learning • XAI
10.1109/ACCESS.2025.3625442
23Kopanja M., Savic M., Longo L.CORTEX: Cost-Sensitive Rule and Tree Extraction Method Knowledge-Based Systems 2025 Explainable artificial intelligence • Rule-based methods • Tree-based methods • Cost-sensitive decision tree • Rule extraction • Surrogate models
10.1016/j.knosys.2025.114592
22Kopanja M., Savic M., Longo LEnhancing Cost-Sensitive Tree-Based XAI Surrogate Method: Exploring Alternative Cost Matrix Formulation Joint Proceedings of the xAI 2025 Late-breaking Work, Demos and Doctoral Consortium co-located with the 3rd World Conference on eXplainable Artificial Intelligence (xAI 2025) 2025 Explainable artificial intelligence • Cost-sensitive decision tree • Surrogate modeling • Rule extraction • Tree-based methods • Model-agnostic explanations • Rule-based systems • Interpretability • Machine Learning.
21Gupta G., Qureshi M.A., Longo L.A Global Post Hoc XAI Method For Interpreting LSTM Using Deterministic Finite State Automata The Irish conference on Artificial Intelligence and Cognitive Science 2025 RNN • interpretability • Explainable AI • LSTM • Deterministic Finite State Automata • k-means clustering • Recurrent Neural Networks
20Mekonnen E.T., Longo L., Dondio P.A global model-agnostic rule-based XAI method based on Parameterized Event Primitives for time series classifiers Frontiers Artificial Intelligence 2024 Deep learning • Explainable Artificial Intelligence • time series classification • decision tree • model agnostic • post-hoc • Machine Learning
10.3389/frai.2024.1381921
19Davydko O., Pavlov V., Biecek P., & Longo L.SRFAMap: A Method for Mapping Integrated Gradients of a CNN Trained with Statistical Radiomic Features to Medical Image Saliency Maps eXplainable Artificial Intelligence, The World Conference (xAI-2024) 2024 Explainable artificial intelligence • Radiomics • Texture analysis • Medical image processing • Saliency map • Deep-learning • machine learning
10.1007/978-3-031-63803-9_1
18Manzoor A. Atif Qureshi M., KidneyE., Longo L.A Review on Machine Learning Methods for Customer Churn Prediction and Recommendations for Business Practitioners IEEE Access 2024 Churn Prediction • Machine Learning • Artificial Intelligence • Business Decision making • Customer Defection • Marketing Analytics • Business Intelligence • Business • Predictive models • Switches • Reviews • Machine learning • Surveys • Profitability
10.1109/ACCESS.2024.3402092
17Raufi B., Longo L.Comparing ANOVA and PowerShap Feature Selection Methods via Shapley Additive Explanations of Models of Mental Workload Built with the Theta and Alpha EEG Band Ratios BioMedInformatics 2024 model explainability • mental workload • statistical feature selection • Shapley-based feature selection • alpha and theta EEG band ratios • machine learning • Deep-learning
10.3390/biomedinformatics4010048
16Mekonnen E.T., Dondio P., Longo L. Explaining Deep Learning Time Series Classification Models using a Decision Tree-Based Post-Hoc XAI Method Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023) 2023 Explainable Artificial Intelligence • Deep Learning • Time Series • Classification • Decision-Trees • Machine Learning • Post-hoc
15Davydko O., Pavlov V., Longo L.Selecting textural characteristics of chest X-Rays for pneumonia lesions classification with the integrated gradients XAI attribution method eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Explainable artificial intelligence • Neural networks • Texture analysis • Medical image processing • Classification • Machine Learning
10.1007/978-3-031-44064-9_36
14Gómez Tapia C., Bozic B., Longo L. Investigating the Effect of Pre-processing Methods on Model Decision-Making in EEG-Based Person Identification eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Electroencephalography • eXplainable Artificial Intelligence • Deep Learning • Signal processing • attribution xAI methods • Graph-Neural Network • Biometrics • signal-to-noise ratio
10.1007/978-3-031-44070-0_7
13Vilone G., Longo L.Development of a Human-Centred Psychometric Test for the Evaluation of Explanations Produced by XAI Methods eXplainable Artificial Intelligence, The World Conference (xAI-2023) 2023 Explainable Artificial Intelligence • Human-centred evaluation • Psychometrics • Machine Learning • Deep Learning • Explainability
10.1007/978-3-031-44070-0_11
12Vilone G. Longo L.A global model-agnostic XAI method for the automatic formation of an abstract argumentation framework and its objective evaluation. 1st Int. Workshop on Argumentation for eXplainable AI (with 9th Int. Conference on Computational Models of Argument, COMMA 2022) 2022 Explainable artificial intelligence • Argumentation • Non-monotonic reasoning • Method evaluation • Metrics of explainability
11Vilone G., Longo L.A Novel Human-Centred Evaluation Approach and an Argument-Based Method for Explainable Artificial Intelligence. Artificial Intelligence Applications and Innovations - 18th IFIP WG 12.5 International Conference 2022 Explainable Artificial Intelligence • Argumentation • Human-centred evaluation • Non-monotonic reasoning • Explainability
10.1007/978-3-031-08333-4_36
10Vilone G., Longo L.A Quantitative Evaluation of Global, Rule-Based Explanations of Post-Hoc, Model Agnostic Methods Frontiers in Artificial Intelligence 2021 explainable artificial intelligence • rule extraction • method comparison and evaluation • metrics of explainability • method automatic ranking • artificial intelligence • explainability
10.3389/frai.2021.717899
9Vilone G., Longo L.Classification of Explainable Artificial Intelligence Methods through Their Output Formats Machine Learning and Knowledge Extraction 2021 explainable artificial intelligence • method classification • systematic literature review
10.3390/make3030032
8Vilone G, Longo L.Notions of explainability and evaluation approaches for explainable artificial intelligence Information fusion 2021 Explainable artificial intelligence • Notions of explainability • Evaluation methods
10.1016/j.inffus.2021.05.009
7Hancock, G. and Longo, L. and Hancock, P. and Young, M.Mental Workload Handbook of human factors & ergonomics 2021 Mental Workload • Cognitive load • Techniques • methods
10.1002/9781119636113.ch7
6Vilone G., Rizzo L., Longo L.A comparative analysis of rule-based, model-agnostic methods for explainable artificial intelligence Proceedings for the 28th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, December 7-8, 2020 2020 Explainable artificial intelligence • Rule extraction • Method • comparison • evaluation
5Orru G., Longo L.Direct and Constructivist Instructional Design: A Comparison of Efficiency Using Mental Workload and Task Performance 4th International Symposium on Human Mental Workload: Models and Applications 2020 Cognitive load theory • Mental workload • Efficiency • Direct instruction methods • Inquiry methods
10.1007/978-3-030-62302-9_7
4Longo L.Empowering Qualitative Research Methods in Education with Artificial Intelligence WCQR 2019: Computer Supported Qualitative Research 2019 Artificial intelligence • Qualitative research Methods • Data analysis • Education • Teaching • Learning • Behaviourism • Constructivism • Cognitivism • Automated reasoning • Knowledge representation • Machine learning • Planning • Perception • Natural language processing
10.1007/978-3-030-31787-4_1
3Longo L, Orru G.An Evaluation of the Reliability, Validity and Sensitivity of Three Human Mental Workload Measures Under Different Instructional Conditions in Third-Level Education McLaren B., Reilly R., Zvacek S., Uhomoibhi J. (eds) Computer Supported Education. CSEDU 2018. 2019 Cognitive Load Theory • Cognitive load types • Human Mental Workload • Instructional design • Direct instructions • Cognitive Theory of Multimedia Learning • Inquiry methods • Community of Inquiry • Reliability • Validity • Sensitivity • Education
10.1007/978-3-030-21151-6_19
2Moustafa K., Luz S., Longo L.Assessment of Mental Workload: A Comparison of Machine Learning Methods and Subjective Assessment Techniques International Symposium on Human Mental Workload: Models and Applications 2017 Mental Workload • Machine Learning • Subjective assessment techniques • Modeling
1Longo L., Kane B.A novel methodology for evaluating user interfaces in health care 24th International Symposium on Computer-Based Medical Systems 2011 Nasa Task Load Index • Usability • Health-care • Mental Workload • Human-Computer Interaction
# Authors Title Details Date Pdf/Links/Bibtex Keywords