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Saada A, Dias SB, Alhussein G, Lyreskog D, Gerasimou I, Alvesc B, de Vos Î, Drivas I, Zaras J, Stergioulas A, Bensenousi B, Hadjileontiadis L, Chatzichristos C, Hadjidimitriou S
Clinical AI is Not (Yet) Trustworthy-But It Could Be
Clinical AI is not (yet) trustworthy-but it could be
Ali Saada;
Sofia B. Dias;
Ghada Alhussein;
David Lyreskog;
Ioannis Gerasimou;
Beatriz Alvesc;
Îśaarten de Vos;
Ioannis Drivas;
John Zaras;
Andreas Stergioulas;
Bensenousi Bensenousi;
Leontios Hadjileontiadis;
Christos Chatzichristos;
Stelios Hadjidimitriou
ABSTRACT
The shift toward trustworthy artificial intelligence (AI) in healthcare marks a pivotal transformation. Traditionally, clinical AI systems have lacked dynamic trust integration across their lifecycle. With structured governance frameworks, AI in healthcare is evolving—ushering in a new era of trust-enabling technologies. In this Viewpoint, we present a framework grounded in the Assessment List for Trustworthy Artificial Intelligence (ALTAI) and applied within the Horizon Europe AI-PROGNOSIS project to embed ethical, technical, and regulatory safeguards across the AI lifecycle. By surfacing implementation tensions and integrating normative, technical, and regulatory safeguards, we outline a replicable path for building adaptive, trust-enabling infrastructures in clinical practice, demonstrating that while clinical AI is not yet trustworthy, structured, lifecycle-oriented governance makes it possible.
Citation
Please cite as:
Saada A, Dias SB, Alhussein G, Lyreskog D, Gerasimou I, Alvesc B, de Vos Î, Drivas I, Zaras J, Stergioulas A, Bensenousi B, Hadjileontiadis L, Chatzichristos C, Hadjidimitriou S
Clinical AI is Not (Yet) Trustworthy-But It Could Be