Consultancy Frameworks for AI-Driven Medical Imaging: Advancing Early Diagnosis in Healthcare Systems

While the integration of AI (artificial intelligence), its application in medical imaging is rapidly changing the world of diagnostics, some health systems have yet to develop specific design guides to offer guidance for how we make AI usage in medical imaging safe and ethically sound, whilst in a way that could scale to a wider context with good security. We now present a consultancy system for AI-driven medical imaging for early diagnosis in Saudi Arabia. Based on international standards like SPIRIT-AI, CONSORT-AI, CLAIM, DECIDE-AI and the WHO Ethics and Governance of AI for Health, the framework covers essential obligations for responsible AI use.

An expert perspective approach was used to gather the expertise in the field by utilizing qualitative design based on healthcare professionals, radiology practitioners, biomedical engineering and digital health specialists deployed in Saudi Arabia. Some of the more specific domains identified in this analysis relate to readiness assessment, workflow integration, interoperability, data governance, cybersecurity, explainable AI (XAI), federated learning, regulatory alignment with FDA, AI Act, and continuous metrics. The results indicate that the successful introduction of AI in medical imaging should be achieved within an organisational consultancy model, with ethical restrictions and technical validation, adaptation of clinical workflow and stakeholder participation. The framework developed provides applicable recommendations for healthcare institutions working to incorporate AI-assisted imaging tools to optimize early diagnosis, enhance efficiency in radiology, as well as to promote global AI governance best practices. We add to the growing digital health literature by providing a contextualized evidence-informed model aimed at supporting strategizing judgments and fast-tracking the move to AI enabled diagnostic platforms in Saudi healthcare systems.

Medical imaging AI-enabled; consultancy frameworks; early diagnosis tools; radiology workflow integration

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