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Vol 4, Issue 2 (2025)
Journal of Trustworthy and Explainable Intelligent Systems
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Vol 4, Issue 2 (2025)
Explainable Machine Learning for COVID-19 Prognosis: Assessing Variant Influence and Clinical Risk Factors
Thabo Nkosi, Lerato Molefe, Sipho Dlamini, Ayanda Mokoena & Kabelo Ndlovu
Original Research
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Open access
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15 September 2025
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Article: 66
Machine Learning in Defense and Military Applications: Opportunities, Challenges, and Ethical Considerations
Lucas Meyer, Anna Schmidt, Stefan Braun & Laura Keller
Original Research
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Open access
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15 September 2025
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Article: 67
Interactive Explainable Fair Machine Learning: A Human-in-the-Loop Framework for Bias Detection and Mitigation
James Walker, Olivia Harris & George Wilson
Original Research
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Open access
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15 September 2025
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Article: 68
Neural Logic Networks for Interpretable Decision Rule Learning: Alternative Formulations and Architectures
Ali Hassan, Noor Siddiqui, Bilal Khan, Sana Malik & Hassan Ali
Original Research
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Open access
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15 September 2025
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Article: 69
Generating Feasible Minimally Contrastive Counterfactual Explanations for Real-Time Decision Support
Chen Hao, Liu Fang, Zhao Lin & Wei Zhang
Original Research
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Open access
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15 September 2025
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Article: 70
Designing Transparent Public Sector AI Systems: Lessons from the UK Algorithmic Transparency Standard
Maria Silva, Joao Pereira, Bruno Costa & Ricardo Alves
Original Research
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Open access
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15 September 2025
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Article: 71
EnAE: An Ensemble Autoencoder Approach to Adversarial Robust Classification
Luis Herrera, Daniela Rojas & Andres Castro
Original Research
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Open access
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15 September 2025
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Article: 72
Continuous User Authentication via Mouse Dynamics Using Machine and Deep Learning Models
Omar Khalid, Sara Nadeem, Bilal Farooq & Hina Saeed
Original Research
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Open access
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15 September 2025
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Article: 73
Building Trustworthiness into Intelligent Systems: From Data Provenance and Model Reliability to Human Control and Institutional Accountability
James Whitfield, Aisha Rahman & Kenji Sato
Original Research
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Open access
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15 September 2025
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Article: 76
Which Explanation for Whom and When? A Stakeholder-Oriented Taxonomy of Global, Local, Counterfactual, Causal, Interactive, and Adaptive Explanations
Laura Mendez, Hiroshi Sato & Anna Kowalczyk
Original Research
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Open access
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15 September 2025
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Article: 77
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