Citation

Nazar, Mobeen and Unar, Salahuddin and Ahmed, Anil and Mohd Su’ud, Mazliham and Alam, Muhammad Mansoor and Rahmat, Azizah (2026) Requirements Driven Explainable Artificial Intelligence Framework for Secure and Transparent Clinical Decision Support Systems. IEEE Access, 14. pp. 29132-29144. ISSN 2169-3536

Text Requirements Driven Explainable Artificial Intelligence Framework for Secure and Transparent Clinical Decision Support Systems.pdf - Published Version Restricted to Repository staff only Download (2MB)

Abstract

In the medical field, where clinical decision support system have a significant impact on vital medical decisions, there is an urgent need for transparent and secure artificial intelligence solutions. This research offers a framework that combines requirement engineering with explainable artificial intelligence methods concepts to improve clinical decision support system security and transparency. The framework uses concern separation goal modeling (Knowledge Acquisition in automated specification), stakeholder analysis (Use Case Modeling), and concern separation (Aspect-Oriented Requirement Engineering) to ensure that system explanations are aligned with stakeholder needs while addressing privacy, compliance, and safety requirements. The proposed approach is evaluated using a real-world medical dataset demonstrating improvements in explanation consistency, requirement alignment, and robustness under security constraints. These results highlight the potential of integrating Requirements Engineering with XAI to support secure, interpretable, and accountable AI-driven clinical decision-making.

Item Type:	Article
Uncontrolled Keywords:	Explainable artificial intelligence
Subjects:	Q Science > Q Science (General) > Q300-390 Cybernetics
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	03 Mar 2026 02:52
Last Modified:	03 Mar 2026 02:52
URII:	http://shdl.mmu.edu.my/id/eprint/15430

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