Artificial Intelligence (AI) has achieved immense progress in recent years across a wide array of application domains, with biomedical imaging and sensing emerging as particularly impactful areas. However, the integration of AI in safety-critical fields, particularly biomedical domains, continues to face a major challenge of explainability arising from the opacity of complex prediction models. Overcoming this obstacle falls within the realm of eXplainable Artificial Intelligence (XAI), which is widely acknowledged as an essential aspect for successfully implementing and accepting AI techniques in practical applications to ensure transparency, fairness, and accountability in the decision-making processes and mitigate potential biases. This article provides a systematic cross-domain review of XAI techniques applied to quantitative prediction tasks, with a focus on their methodological relevance and potential adaptation to biomedical imaging and sensing. To achieve this, following PRISMA guidelines, we conducted an analysis of 44 Q1 journal articles that utilised XAI techniques for prediction applications across different fields where quantitative databases were used, and their contributions to explaining the predictions were studied. As a result, 13 XAI techniques were identified for prediction tasks. Shapley Additive eXPlanations (SHAP) was identified in 35 out of 44 articles, reflecting its frequent computational use for feature-importance ranking and model interpretation. Local Interpretable Model-Agnostic Explanations (LIME), Partial Dependence Plots (PDPs), and Permutation Feature Index (PFI) ranked second, third, and fourth in popularity, respectively. The study also recognises theoretical limitations of SHAP and related model-agnostic methods, such as their additive and causal assumptions, which are particularly critical in heterogeneous biomedical data. Furthermore, a synthesis of the reviewed studies reveals that while many provide computational evaluation of explanations, none include structured human–subject usability validation, underscoring an important research gap for clinical translation. Overall, this study offers an integrated understanding of quantitative XAI techniques, identifies methodological and usability gaps for biomedical adaptation, and provides guidance for future research aimed at safe and interpretable AI deployment in biomedical imaging and sensing.

Since the advent of a circular economy, typical strategies for change have focused on circularising existing business models or developing new closed-loop ones, where design is understood as a service provider, adapting its processes accordingly. This understanding and application of design is problematical, constraining and misdirecting any potential for effective innovation in the future. Interior design methodology needs to be completely rethought to create a sustainable circular design ecosystem. The learning and teaching of the interior design process has its foundation in an unsustainable, traditional economy that operates in a closed linear sequence of design, specification and fit-out. An undergraduate retail interior design project highlighted the need to evaluate designing for a circular economy as an ecosystem, based on the 10 R’s leading to four building blocks for the learning and teaching of circular retail interior design. Through analysis of the nature and existing use of design within a circular economy, it is possible to conceptualise the deconstruction of the existing linear process of interior design pedagogy and rebuild that process as a sustainable circular retail interior design methodology. This paper identifies four key sustainable design principles as a foundation for a new education paradigm for a circular interior design ecosystem model.

This paper discusses a theory for the foundation of design for pedagogy based on the principles of pattern languages. We develop a pattern using a variation of the Alexandrian pattern structure to embed pedagogy at the core of the design of e-learning. A pattern dealing with the organization of an online discussion group based on the principles of constructivism and experiential learning is produced to illustrate the application of the theory.

"Embedding Pedagogical Principles and Theories into Design Patterns" published on 01 Jan 2010 by Brill.