AI tools are transforming healthcare—but not without risks. One of the most thought-provoking questions was about the difference between hallucinations and confabulations in AI—and why that distinction matters.
In clinical settings, the consequences of misinformation can be serious. Whether fabricated or distorted, inaccurate AI outputs can lead to misdiagnoses, inappropriate treatments, and a loss of trust in digital tools. That’s why distinguishing between hallucinations and confabulations is more than academic—it’s essential for patient safety.
Five ways to prevent AI hallucinations and confabulations: 1.Use high-quality, domain-specific training data. 2.Implement robust validation and testing. 3.Incorporate human oversight. 4.Use confidence scoring and explainability. 5.Restrict outputs to verified knowledge sources.
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