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Aligning Artificial Intelligence Prediction Targets with Clinical Workflows Using Human Centered Design Methods

2026-01-16 health informatics Title + abstract only
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Artificial intelligence models in healthcare often fail to improve patient outcomes despite strong predictive performance because they are frequently developed with limited understanding of clinical workflows and system implementation. We demonstrate a human-centered design approach to define prediction targets before model development, ensuring alignment with actionable clinical interventions. Using pediatric acute kidney injury as a case study, we convened a multidisciplinary working group and...

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