Mohammad Naiseh

How the different explanation classes impact trust calibration: The case of clinical decision support systems

2022 · 112 Zit. · International Journal of Human-Computer Studies

Personalising Explainable Recommendations: Literature and Conceptualisation

2020 · 38 Zit. · Advances in intelligent systems and computing

Explainable Recommendations and Calibrated Trust: Two Systematic User Errors

2021 · 26 Zit. · Computer

C-XAI: A conceptual framework for designing XAI tools that support trust calibration

2024 · 20 Zit. · Journal of Responsible Technology

Explainable Recommendations in Intelligent Systems: Delivery Methods, Modalities and Risks

2020 · 20 Zit. · Lecture notes in business information processing

Trustworthy Autonomous Systems (TAS): Engaging TAS experts in curriculum design

2022 · 8 Zit. · 2022 IEEE Global Engineering Education Conference (EDUCON)

Explainability Design Patterns in Clinical Decision Support Systems

2020 · 7 Zit. · Lecture notes in business information processing

Trustworthy Autonomous Systems (TAS): Engaging TAS experts in curriculum design

2022 · 4 Zit. · arXiv (Cornell University)

Social eXplainable AI (Social XAI): Towards Expanding the Social Benefits of XAI

2024 · 3 Zit. · Studies in neuroscience, psychology and behavioral economics

Health care professionals’ perceptions of machine learning based clinical decision support systems for oesophageal cancer management

2025 · 0 Zit. · Computers in Biology and Medicine

A UK perspective on responsible education for responsible AI: a multidisciplinary review and evaluation framework

2025 · 0 Zit. · Journal of Responsible Technology

Trusting machines? Cross-sector lessons from healthcare & security: conference report

2021 · 0 Zit.