AI innovation in healthcare is on the rise, but the reliability of AI tools and confidence scores is under scrutiny. While confidence scores are used to measure AI reliability in healthcare, they often rely on approximations rather than proven probabilities, leading to potential misleading results. Blindly trusting confidence scores can create risks, especially for healthcare professionals who may not fully understand the technology. Instead of relying on confidence scores, experts recommend localizing and updating AI models, thoughtfully displaying outputs for end users, and supporting clinical judgment rather than replacing it. By blending AI insights with real-world context, organizations can use AI responsibly for safer patient care.
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