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Recently, the integration of artificial intelligence (AI) in optimizing healthcare supply chains (HSC) has gained increasing attention, particularly concerning sustainability indicators in developing countries like Tunisia. This paper presents a framework for an AI-Driven Dashboard (AI-D) designed to track and optimize indicators within HSCs. By integrating data from various sources, the AI-D aims to provide healthcare managers with real-time insights, enabling better resource allocation and fostering more sustainable practices. In this study, sustainability indicators pertinent to the AI-D were contextually set and rigorously prioritized using expert consensus and fuzzy logic to attend to Tunisia's specific health challenges. The framework proposed will provide decision support using AI to optimize resource allocation, minimize waste, and align HSC with global sustainability goals.

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Toward an AI-Driven Dashboard Framework for Assessing the Sustainability of Healthcare Supply Chains: A Case Study in Tunisia

  • 会议论文

  • 发表日期：

    2026年

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  • Asma Fekih

摘要

Recently, the integration of artificial intelligence (AI) in optimizing healthcare supply chains (HSC) has gained increasing attention, particularly concerning sustainability indicators in developing countries like Tunisia. This paper presents a framework for an AI-Driven Dashboard (AI-D) designed to track and optimize indicators within HSCs. By integrating data from various sources, the AI-D aims to provide healthcare managers with real-time insights, enabling better resource allocation and fostering more sustainable practices. In this study, sustainability indicators pertinent to the AI-D were contextually set and rigorously prioritized using expert consensus and fuzzy logic to attend to Tunisia's specific health challenges. The framework proposed will provide decision support using AI to optimize resource allocation, minimize waste, and align HSC with global sustainability goals.