Artificial intelligence, bias and clinical safety
An analysis on AI bias and clinical safety argues that machine learning-based diagnostic decision support must be assessed with the same rigor as new laboratory tests. The authors warn that biased training data and opaque models can lead to unsafe or inequitable recommendations, and they advocate for systematic evaluation frameworks to protect patient safety in biased medical AI systems.
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LOG Standards provides an independent accreditation signal for AI models used in healthcare, helping hospitals, care networks, and AI companies bring clinical AI readiness and governance into clearer conversations.
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