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Artificial intelligence should genuinely support clinical reasoning and decision making to bridge the translational
Kacper Sokol1, James Fackler2,3, Julia E Vogt4
1Department of Computer Science, ETH Zurich, Zurich, Switzerland. kacper.sokol@inf.ethz.ch.
Abstract:
Artificial intelligence promises to revolutionise medicine, yet its impact remains limited because of the pervasive translational gap. We posit that the prevailing technology-centric approaches underpin this challenge, rendering such systems fundamentally incompatible with clinical practice, specifically diagnostic reasoning and decision making. Instead, we propose a novel sociotechnical conceptualisation of data-driven support tools designed to complement doctors' cognitive and epistemic activities. Crucially, it prioritises real-world impact over superhuman performance on inconsequential benchmarks.
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