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A timing flaw in sepsis AI studies could mislead care decisions
Researchers say a common data-processing mistake in reinforcement-learning studies of sepsis can inflate model performance and could lead to over- or undertreatment if deployed clinically.
Key Takeaways
- A new paper identifies a widespread timing error in sepsis AI research.
- The flaw can make models look better by leaking future information into past predictions.
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DT Editorial Team··via medicalxpress.com
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