Explainable artificial intelligence: an analytical review

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1. Evaluation of XAI Models for Interpretation of Deep Learning Techniques’ Results in Automated Plant Disease Diagnosis
   Marco de Benito Fernández, Daniel López Martínez, Alfonso González‐Briones, Pablo Chamoso, Emilio Corchado · 2023 · Lecture notes in networks and systems
2. Compare-xAI: Toward Unifying Functional Testing Methods for Post-hoc XAI Algorithms into a Multi-dimensional Benchmark
   Mohamed Karim Belaid, Richard Bornemann, Maximilian Rabus, Ralf Krestel, Eyke Hüllermeier · 2023 · Communications in computer and information science
3. Defending the Cloud: Understanding the Role of Explainable AI in Intrusion Detection Systems
   Utsav Upadhyay, Alok Kumar, Satyabrata Roy, Umashankar Rawat, Sandeep Chaurasia · 2023 · International Conference on Security of Information and Networks (SIN)
4. Artificial Intelligence Algorithms in Flood Prediction: A General Overview
   Manish Kumar Pandey · 2024 · Springer eBooks
5. FairXAI - A Taxonomy and Framework for Fairness and Explainability Synergy in Machine Learning
   Resmi Ramachandranpillai, Ricardo A. Baeza-Yates, Fredrik Heintz · 2025 · IEEE Transactions on Neural Networks and Learning Systems
6. Digital supply chain surveillance
   Alexandra Melike Brintrup, Edward Elson Kosasih, Bart L. MacCarthy, Güven Demirel · 2022 · Elsevier eBooks
7. A context-aware decision support system for selecting explainable artificial intelligence methods in business organizations
   Marcelo Índio dos Reis, João N.C. Gonçalves, Paulo Cesar Cortez, Maria Sameiro Carvalho, Joao Miguel Fernandes · 2024 · Computers in Industry
8. Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence
   Yasin Görmez, Fatma Hilal Yağın, Burak Yagin, Yalın Aygün, Hulusi Böke, Georgian Bădicu, Matheus Santos de Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei · 2025 · Frontiers in Physiology
9. An Urban Population Health Observatory for Disease Causal Pathway Analysis and Decision Support: Underlying Explainable Artificial Intelligence Model
   Whitney S Brakefield, Nariman Ammar, Arash Shaban‐Nejad · 2022 · JMIR Formative Research
10. Social-Aware Federated Learning: Challenges and Opportunities in Collaborative Data Training
    Abdul-Rasheed Olatunji Ottun, Pramod C. Mane, Zhigang Yin, Souvik Paul, Mohan Liyanage, Jason Pridmore, Aaron Yi Ding, Rajesh R. Sharma, Petteri Nurmi, Huber Flores · 2022 · IEEE Internet Computing
11. Decoding the Black Box: A Comprehensive Review of Explainable Artificial Intelligence
    Ossama H. Embarak · 2023 · International Conference on Information Technology Trends (ITT)
12. A unified and practical user-centric framework for explainable artificial intelligence
    Sinan Kaplan, Hannu M. T. Uusitalo, Lasse T. Lensu · 2023 · Knowledge-Based Systems
13. Global Paradigm Shifts in Urban Stormwater Management Optimization: A Bibliometric Analysis
    Mo Wang, Zhiyu Jiang, Rana Muhammad Adnan Ikram, Chuanhao Sun, Menghan Zhang, Jianjun Li · 2023 · Water
14. Explain to Me: Salience-Based Explainability for Synthetic Face Detection Models
    Colton R. Crum, Patrick Tinsley, Aidan Boyd, Jacob C. Piland, Christopher R. Sweet, Timothy Kelley, Kevin W. Bowyer, Adam Czajka · 2023 · IEEE Transactions on Artificial Intelligence
15. Explainable Transfer Learning for Modeling and Assessing Risks in Tunnel Construction
    Hanbin Luo, Jialin Chen, Peter E.D. Love, Weili Fang · 2024 · IEEE Transactions on Engineering Management
16. Machine Learning and Deep Learning Strategies for Chinese Hamster Ovary Cell Bioprocess Optimization
    Tiffany-Marie D. Baako, S Kulkarni, Jerome L. McClendon, Sarah W. Harcum, Jordon Gilmore · 2024 · Fermentation
17. Explainable deep learning for sEMG-based similar gesture recognition: A Shapley-value-based solution
    Feng Wang, Xiaohu Ao, Min Hua Wu, Seiichi Kawata, Jinhua She · 2024 · Information Sciences
18. The Application Potential of Artificial Intelligence and Numerical Simulation in the Research and Formulation Design of Drilling Fluid Gel Performance
    Keming Sheng, Yinbo He, Mingliang Du, Guancheng Jiang · 2024 · Gels
19. Platelet Metabolites as Candidate Biomarkers in Sepsis Diagnosis and Management Using the Proposed Explainable Artificial Intelligence Approach
    Fatma Hilal Yağın, Umran Aygun, Abdulmohsen Algarni, Cemil Çolak, Fahaid H. Al-Hashem, Luca Paolo Ardigò · 2024 · Journal of Clinical Medicine
20. Fair and explainable Myocardial Infarction (MI) prediction: Novel strategies for feature selection and class imbalance correction
    Simon Bin Akter, Sumya Akter, Moon Das Tuli, David Eisenberg, Aaron Lotvola, Humayera Islam, Jorge E. Fresneda, Maik Hüttemann, Tanmoy Sarkar Pias · 2024 · Computers in Biology and Medicine
21. A general framework for interpretable neural learning based on local information-theoretic goal functions
    Abdullah Makkeh, Marcel Graetz, Andreas C. Schneider, David A. Ehrlich, Viola Priesemann, Michael Wibral · 2025 · Proceedings of the National Academy of Sciences
22. Data-driven modeling of CO2 capture in rotating packed beds enhanced by carbonic anhydrase using explainable artificial intelligence methods
    Theofilos Xenitopoulos, Αθανάσιος Ι. Παπαδόπουλος, Panos Seferlis · 2025 · Fuel
23. Transparent and Interpretable State of Health Forecasting of Lithium-Ion Batteries with Deep Learning and Saliency Maps
    Friedrich von Bülow, Yannik Hahn, Richard Meyes, Tobias Meisen · 2023 · International Journal of Energy Research
24. Can Explainable Artificial Intelligence Optimize the Data Quality of Machine Learning Model? Taking Meibomian Gland Dysfunction Detections as a Case Study
    Han Wang, Ruoyu Zhou, Zhiyuan Lin, Yang Yu, Peijin Zeng, Xiaoxiao Fang, Jie Yang, Guanghui Hou, Yonghao Li, Xiangrong Yu et al. · 2023 · Journal of Physics Conference Series
25. Quantifying overheating risk in English schools: A spatially coherent climate risk assessment
    Laura C. Dawkins, Kate Brown, Dan J. Bernie, Jason A. Lowe, Theo Economou, Duncan Grassie, Yair Schwartz, Daniel Godoy-Shimizu, Ivan Korolija, Dejan Mumovic et al. · 2024 · Climate Risk Management
26. Attention Analysis in Robotic-Assistive Therapy for Children With Autism
    Bárbara Silva, Laura Santos, Catarina Barata, Alice Geminiani, Gabriele Fassina, Ana Rita Gonzalez, Sara Ferreira, Bernardo Barahona-Corrêa, Ivana Olivieri, Alessandra Pedrocchi et al. · 2024 · IEEE Transactions on Neural Systems and Rehabilitation Engineering
27. Explainable Machine Learning and Graph Neural Network Approaches for Predicting Employee Attrition
    Christopher Makanga, Dennis Mukwaba, Clare Linda Agaba, Sudi Murindanyi, Tibakanya Joseph, Nakayiza Hellen, Ggaliwango Marvin · 2024 · International Conference on Contemporary Computing
28. Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent
    Alejandra de la Rica Escudero, Eduardo C. Garrido‐Merchán, María Coronado Vaca · 2025 · PLoS ONE
29. Informed Machine Learning: Excess risk and generalization
    Luca Oneto, Sandro Ridella, Davide Anguita · 2025 · Neurocomputing
30. An Interpretable Deep Semantic Segmentation Method for Earth Observation
    Ziyang Zhang, Plamen Parvanov Angelov, Eduardo Almeida Soares, Nicolas Longépé, Pierre-Philippe Mathieu · 2022 · IEEE International Conference on Intelligent Systems
31. Interpretation of the effect of transient process data on part quality of injection molding based on explainable artificial intelligence
    Jinsu Gim, Lih‐Sheng Turng · 2023 · International Journal of Production Research
32. A review of image processing and analysis of computed tomography images using deep learning methods
    Darcie Anderson, Prabhakar Ramachandran, Jamie Trapp, Andrew L. Fielding · 2025 · Physical and Engineering Sciences in Medicine
33. Spatial sampling, data models, spatial scale and ontologies: Interpreting spatial statistics and machine learning applied to satellite optical remote sensing
    Peter M. Atkinson, Alfred Stein, C. Jeganathan · 2022 · Spatial Statistics
34. Intrinsic Explainability for End-to-End Object Detection
    Luís Fernandes, João N. D. Fernandes, Mariana Calado, João Ribeiro Pinto, Ricardo Cerqueira, Jaime S. Cardoso · 2023 · IEEE Access
35. On the evaluation of deep learning interpretability methods for medical images under the scope of faithfulness
    Vangelis Lamprou, Athanasios Kallipolitis, Ilias G. Maglogiannis · 2024 · Computer Methods and Programs in Biomedicine
36. A novel framework for crash frequency prediction: Geographic support vector regression based on agent-based activity models in Greater Melbourne
    Quynh Duong, Hulya Gilbert, Hien Nguyen · 2024 · Accident Analysis & Prevention
37. Transparency and Explainability for Public Policy
    Kate Vredenburgh · 2024 · LSE Public Policy Review
38. A Meta-Learning-Based Ensemble Model for Explainable Alzheimer’s Disease Diagnosis
    Fatima Hasan Al-bakri, Wan Mohd Yaakob Wan Bejuri, Mohammed Nasser Al-Andoli, Raja Rina Raja Ikram, Hui Min Khor, Zulkifli Tahir, The Alzheimer’s Disease Neuroimaging Initiative · 2025 · Diagnostics
39. Comparison of traditional machine learning and neural network approaches for automated scoring of second language English essays
    Erik Voss · 2025 · Language Testing
40. Karl Jaspers and artificial neural nets: on the relation of explaining and understanding artificial intelligence in medicine
    Georg Starke, Christopher J. Poppe · 2022 · Ethics and Information Technology
41. Case-study Led Investigation of Explainable AI (XAI) to Support Deployment of Prognostics in the industry
    Omnia Amin, Blair Brown, Bruce Stephen, S.D.J. McArthur · 2022 · PHM Society European Conference
42. At the intersection of human and algorithmic decision-making in distributed learning
    Paul Prinsloo, Sharon Slade, Mohammad Khalil · 2022 · Journal of Research on Technology in Education
43. A Conceptual Framework for Explainability Requirements in Software-Intensive Systems
    Marcello M. Bersani, Matteo Camilli, Livia Lestingi, Raffaela Mirandola, Matteo Rossi, Patrizia Scandurra · 2023 · IEEE International Requirements Engineering Conference Workshops (REW)
44. Fuzzy Cognitive Maps for Interpretable Image-based Classification
    Georgia Sovatzidi, Michael D. Vasilakakis, Dimitris K. Iakovidis · 2022 · IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
45. Consolidated Bioprocessing of Lignocellulosic Biomass: A Review of Experimental Advances and Modeling Approaches
    Mark Korang Yeboah, Dirk Söffker · 2026 · Bioresources and Bioproducts
46. Interpreting the antecedents of a predicted output by capturing the interdependencies among the system features and their evolution over time
    Sonia Farhana Nimmy, Farookh Khadeer Hussain, Ripon Kumar Chakrabortty, Farookh Khadeer Hussain, Morteza Saberi · 2022 · Engineering Applications of Artificial Intelligence
47. Learning to Comprehend and Trust Artificial Intelligence Outcomes: A Conceptual Explainable AI Evaluation Framework
    Peter E. D. Love, J. Matthews, Wei-Li Fang, Stuart Porter, Hanbin Luo, Lie-Yun Ding · 2024 · IEEE Engineering Management Review
48. Enhancing Transparency and Interpretability in Deep Learning Models: A Comprehensive Study on Explainable AI Techniques
    Dr.Shashank Singh, Dhirendra Pratap Singh, Mr.Kaushal Chandra · 2024 · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
49. Enhancing high-school dropout identification: a collaborative approach integrating human and machine insights
    Okan Bulut, Tarid Wongvorachan, Surina He, Soo Lee · 2024 · Discover Education
50. Classifying binary black holes from Population III stars with the Einstein Telescope: A machine-learning approach
    Filippo Santoliquido, Ulyana Dupletsa, Jacopo Tissino, M. Branchesi, Francesco Iacovelli, Giuliano Iorio, Michela Mapelli, Davide Gerosa, J. Harms, Mario Pasquato · 2024 · Astronomy and Astrophysics
51. YAPAY ZEKANIN DENETİMDE KULLANILMASI VE ETİK SORUNLAR
    Mehmet Polat · 2024 · Sayıştay Dergisi
52. Model-agnostic counterfactual explanation: A feature weights-based comprehensive causal multi-objective counterfactual framework
    Jinping Liu, Xiaoqiang Wu, Shiyi Liu, Subo Gong · 2024 · Expert Systems with Applications
53. Feasibility and time gain of implementing artificial intelligence-based delineation tools in daily magnetic resonance image-guided adaptive prostate cancer radiotherapy
    Maximilian Konrad, Carsten Brink, Anders Smedegaard Bertelsen, Ebbe Laugaard Lorenzen, Bahar Çelik, Christina Junker Nyborg, Lars Dysager, Tine Schytte, Uffe Bernchou · 2024 · Physics and Imaging in Radiation Oncology
54. Explainable artificial intelligence and advanced feature selection methods for predicting gas concentration in longwall mining
    Haoqian Chang, Xiangqian Wang, Alexandra Ioana Cristea, Xiangrui Meng, Zuxiang Hu, Ziqi Pan · 2025 · Information Fusion
55. Explainable artificial intelligence (xAI) applied to deep computer vision of microscopy imaging and spectroscopy for assessment of oleogel stability over storage
    Ingrid Alves de Moraes, Leonardo Arrighi, Sylvio Barbon, Javier E.L. Villa, Rosiane Lopes Cunha, Douglas Fernandes Barbin · 2025 · Journal of Food Engineering
56. Why decision support systems are needed for addressing the theory-practice gap in assembly line balancing
    Christoffer Fink, Ulf Bodin, Olov Schelén · 2025 · Journal of Manufacturing Systems
57. From scientific theory to duality of predictive artificial intelligence models
    Jürgen Bajorath · 2025 · Cell Reports Physical Science
58. A look into how machine learning is reshaping engineering models: the rise of analysis paralysis, optimal yet infeasible solutions, and the inevitable Rashomon paradox
    Mohannad Zeyad Naser · 2025 · Machine learning for computational science and engineering
59. Resonance-Based Optical Gas Sensors
    Elieser Ernesto Gallego Martínez, Carlos R. Zamarreño, Ignacio Raul Matias · 2025 · IEEE Sensors Reviews
60. Exploring the complex associations between community public spaces and healthy aging: an explainable analysis using catboost and SHAP
    Man Zhang, Tao Shen, Ying Li, Qianqian Li, Yongqi Lou · 2025 · BMC Public Health
61. Fuzzy similarity phrases for interpretable data classification
    Michael D. Vasilakakis, Dimitris K. Iakovidis · 2023 · Information Sciences
62. When to choose ranked area integrals versus integrated gradient for explainable artificial intelligence – a comparison of algorithms
    Vinay Kumar Singh, Iuliia Konovalova, Arpan Kumar Kar · 2022 · Benchmarking An International Journal
63. Making the Black Box Transparent: State of the Art in Explainable Machine Learning for Structural Design and Assessment
    Mohsen Zaker Esteghamati, Jingcheng Wang, Xiaowei Wang, Stephanie German Paal, Jacob Dylan Murphy, Ali Namin, Abdullahi Salman, Adam Ado Sabari, Muhammad Ahsan Ibrar, Ram Krishna Mazumder et al. · 2026 · Journal of Structural Engineering
64. Explainable Artificial Intelligence in Drones: A Brief Review
    Omar Banimelhem, Baghdad Al‐khateeb · 2023 · International Conference on Information and Communication Systems (ICICS)
65. Learning spatio-temporal patterns with Neural Cellular Automata
    Alex D. Richardson, Tibor Antal A, Richard A. Blythe, Linus J. Schumacher · 2024 · PLoS Computational Biology
66. Machine learning to model gentrification: A synthesis of emerging forms
    Mueller Maya, Simi Hoque, Hamil Pearsall · 2024 · Computers Environment and Urban Systems
67. Explainable AI in Healthcare
    Shantha Visalakshi Upendran · 2024 · Advances in healthcare information systems and administration book series
68. Hybrid Feature Mammogram Analysis: Detecting and Localizing Microcalcifications Combining Gabor, Prewitt, GLCM Features, and Top Hat Filtering Enhanced with CNN Architecture
    Miguel Alejandro Hernández-Vázquez, Yazmín Mariela Hernández-Rodríguez, Fausto David Cortes-Rojas, Rafael Bayareh-Mancilla, Oscar Eduardo Cigarroa-Mayorga · 2024 · Diagnostics
69. Roadmap on industrial imaging techniques
    Jung‐Ryul Lee, Hongki Yoo, Chen Ciang Chia, Young‐Jin Kim, Daehee KIM, Teow Wee Teo, Zeinab Mahdavipour, Azizi Abdullah, Bee Ee Khoo, Mohd Zaid Abdullah et al. · 2024 · Measurement Science and Technology
70. TPat: Transition pattern feature extraction based Parkinson’s disorder detection using FNIRS signals
    Türker Tuncer, İrem Taşçı, Burak Taşçı, Rena Hajiyeva, Ilknur Tuncer, Şengül Doğan · 2024 · Applied Acoustics
71. AI-based analysis of fetal growth restriction in a prospective obstetric cohort quantifies compound risks for perinatal morbidity and mortality and identifies previously unrecognized high risk clinical scenarios
    Raquel Mae Zimmerman, Edgar Javier Hernandez, Mark D. Yandell, Martin Tristani‐Firouzi, Robert M. Silver, William A. Grobman, David M. Haas, George A. Saade, Jon G. Steller, Nathan R. Blue · 2025 · BMC Pregnancy and Childbirth
72. Inferring causal associations in hydrological systems: a comparison of methods
    Hanxu Liang, Wensheng Wang, Dedi Liu, Bin Chen, Li Guo, Hu Liu, Siyi Yu, Dan Zhang · 2025 · Stochastic Environmental Research and Risk Assessment
73. An Explainable Machine Learning-Based Employee Attrition Predictive System
    Md Amir Hamja, Mahmudul Hasan, Ziaul Hassan, Md Palash Uddin, Md. Jahangir Alam Siddikee · 2025 · Annals of Data Science
74. Explainable AI for online disinformation detection: Insights from a design science research project
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75. Visualizing Paired Image Similarity in Transformer Networks
    Samuel Black, Abby Stylianou, Robert B. Pless, Richard Souvenir · 2022 · IEEE Winter Conference on Applications of Computer Vision
76. Automatic Fuzzy Graph Construction For Interpretable Image Classification
    Georgia Sovatzidi, Michael D. Vasilakakis, Dimitris K. Iakovidis · 2022 · Proceedings - International Conference on Image Processing
77. An Explainable Framework to Predict Child Sexual Abuse Awareness in People Using Supervised Machine Learning Models
    Krishnaraj Chadaga, Srikanth Prabhu, Niranjana Sampathila, Rajagopala Chadaga, Giliyar Muralidhar Bairy, K. S. Swathi · 2023 · Journal of Technology in Behavioral Science
78. eXplainable artificial intelligence applied to algorithms for disruption prediction in tokamak devices
    Luca Bonalumi, Enrico Aymerich, Edoardo Alessi, B. Cannas, Alessandra Fanni, E. Lazzaro, S. Nowak, Fabio Pisano, Giuliana Sias, Carlo Sozzi · 2024 · Frontiers in Physics
79. Fuzzy Linguistic Summaries for Explaining Online Semi-Supervised Learning
    Katarzyna Kaczmarek‐Majer, Gabriella Casalino, Giovanna Castellano, Daniel Furtado Leite, Olgierd Hryniewicz · 2022 · IEEE International Conference on Intelligent Systems
80. Explainable Artificial Intelligence: A Study of Current State-of-the-Art Techniques for Making ML Models Interpretable and Transparent
    Ayush Thakur, Rashmi Vashisth, Sudhanshu Tripathi · 2023 · International Conference on Technological Advancements in Computational Sciences (ICTACS)
81. Explanation-driven Self-adaptation using Model-agnostic Interpretable Machine Learning
    Francesco Renato Negri, Niccolò Nicolosi, Matteo Camilli, Raffaela Mirandola · 2024 · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)
82. An Analytical Review: Explainable AI for Decision Making in Finance Using Machine Learning
    Tanvi Shah, Kishori Shekokar, Amit Barve, Pramod Khandare · 2024 · Parul International Conference on Engineering and Technology (PICET)
83. EX-CODE: A Robust and Explainable Model to Detect AI-Generated Code
    Luana Bulla, Alessandro Midolo, Misael Mongiovı̀, Emiliano Tramontana · 2024 · Information
84. Interpretable credit scoring based on an additive extreme gradient boosting
    Yao Zou, Meng Xia, Xingyu Lan · 2025 · Chaos Solitons & Fractals
85. Framing what can be explained - an operational taxonomy for explainability needs
    Jakob Droste, Hannah Deters, Martin Obaidi, Jil Klünder, Kurt A. Schneider · 2025 · Requirements Engineering
86. SHAP-based interpretable machine learning for predicting the oxide double perovskite band gaps
    Yongxin Cui, Hong-an Lu, Jieru Sun, Qian Zou, Junhao Ma, Chonggui Zhong, Huailiang Fu, Lei Zhang, Pengxia Zhou · 2025 · Physica Scripta
87. Seasonal heatwave forecasting with explainable machine learning and remote sensing data
    Jung-Ching Kan, Marlon Vieira Passos, Georgia Destouni, Karina Barquet, Carla Ferreira, Zahra Kalantari · 2025 · Stochastic Environmental Research and Risk Assessment
88. Basic Issues and Challenges on Explainable Artificial Intelligence (XAI) in Healthcare Systems
    Idowu Dauda Oladipo, Joseph Bamidele Awotunde, Muyideen AbdulRaheem, Shakirat Aderonke Salihu · 2022 · Advances in medical technologies and clinical practice book series
89. Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
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90. Parameter tuning of continuous Hopfield network applied to combinatorial optimization
    Safae Rbihou, Nour‐Eddine Joudar, Khalid Haddouch · 2023 · Annals of Mathematics and Artificial Intelligence
91. Image-based 3D reconstruction and permeability modelling of rock using enhanced interpretable deep residual learning
    Shan Lin, Miao Dong, Zenglong Liang, Hongwei Guo, Hong Zheng · 2024 · Engineering Analysis with Boundary Elements
92. From Virtual Worlds to Real-World Impact: An Industrial Metaverse Survey
    Michael Prummer, Emanuel Regnath, Saurabh Singh, Harald Kosch A · 2024 · Lecture notes in networks and systems
93. Towards algorithms and models that we can trust: A theoretical perspective
    Luca Oneto, Sandro Ridella, Davide Anguita · 2024 · Neurocomputing
94. Generating interpretable rainfall-runoff models automatically from data
    Travis Adrian Dantzer, Branko Kerkez · 2023 · Advances in Water Resources
95. Development of a Classification Model for Predicting Student Payment Behavior Using Artificial Intelligence and Data Science Techniques
    Henry Villarreal-Torres, Julio Ángeles-Morales, William Joel Marín Rodriguez, Daniel Andrade-Girón, Edgardo Carreño-Cisneros, Jenny Cano-Mejía, Carmen Mejía-Murillo, Mariby Boscán, Gumercindo Flores Reyes, Oscar Cruz-Cruz · 2023 · ICST Transactions on Scalable Information Systems
96. On Trustworthy Decision-Making Process of Human Drivers From the View of Perceptual Uncertainty Reduction
    Huanjie Wang, Haibin Liu, Wenshuo Wang, Lijun Sun · 2023 · IEEE Transactions on Intelligent Transportation Systems
97. A Literature Review and Research Agenda on Explainable Artificial Intelligence (XAI)
    Kalyanathaya, Krishna Prakash, K., Krishna Prasad · 2022 · International Journal of Applied Engineering and Management Letters
98. Human knowledge models: Learning applied knowledge from the data
    Egor Dudyrev, Ilia Semenkov, Sergei O. Kuznetsov, Gleb Gusev, Andrew Sharp, Oleg S. Pianykh · 2022 · PLoS ONE
99. Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization
    Nijat Mehdiyev, Maxim Majlatow, Peter Fettke · 2024 · Cognitive Computation
100. Spatial Computing Opportunities in Biomedical Decision Support: The Atlas-EHR Vision
     Majid Farhadloo, Arun Sharma, Shashi Shekhar, Svetomir N. Markovic · 2024 · ACM Transactions on Spatial Algorithms and Systems