Decentralized healthcare with AI: challenges and opportunities

Résumé fourni par la source

Decentralized healthcare is reshaping how, where, and by whom medical imaging is performed. As diagnostic workflows move beyond hospital walls, point-of-care ultrasound (POCUS) is emerging as a central technology enabling this transformation—affordable, portable, and now increasingly intelligent. Yet, despite its promise, widespread adoption is constrained by variability in image quality, operator dependency, and limited data integration across clinical settings. In this keynote, I will discuss how recent advances in artificial intelligence (AI) are addressing these challenges through automated image enhancement, interpretation, and data scaling—turning POCUS into a reliable, high-quality, AI-ready modality for early disease detection and longitudinal monitoring. I will highlight key opportunities in leveraging AI-powered ultrasound for equitable access, large-scale data generation, and remote diagnostics, while also examining technical, regulatory, and ethical barriers that must be overcome to ensure safe and effective decentralization of care.

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