Clinical decision-making is often challenged by noisy data and conflicting diagnostic criteria. In this talk, I will show how artificial intelligence can support clinicians when information is misleading or incomplete. By detecting pathologies in medical data and applying multi-criteria decision-making techniques, AI can highlight inconsistencies and suggest ways to resolve conflicting criteria. This approach does not replace the doctor but enhances their ability to make transparent and robust decisions. I will briefly outline a vision where AI acts as a co-pilot in healthcare, improving safety, efficiency, and trust in clinical decision-making.
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