What do we need to build explainable AI systems for the medical domain?

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Explainable AI for Medicine: Making Smart Tools You Can Trust

Hospitals are using AI more and more, but when a computer gives an answer people want to know why.
We need explainable systems so doctors and patients can feel safe.
These systems should show how a decision was reached, not just give a score.
That builds trust and helps clinicians check results quickly.
AI helps read medical images, find patterns in genetic tests and sort medical notes, yet many tools act like closed boxes.
Without simple explanations, doctors relies on guesses and patients worried.
Laws about data and privacy push for clear, traceable answers, and hospitals want tools that support, not replace, judgement.
Transparent AI can improve patient safety by making errors easier to spot and fix.
Designing such tools means focusing on clear outputs, easy checks and simple ways to retrace a decision.
People will use smart tools more when they understand them, and medicine will benefitt when technology speaks plain words, not riddles.