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Unmasking bias in artificial intelligence: a systematic review of bias detection and mitigation strategies in electronic health record-based models
120
Zitationen
5
Autoren
2024
Jahr
Abstract
This review highlights evolving strategies to mitigate bias in EHR-based AI models, emphasizing the urgent need for both standardized and detailed reporting of the methodologies and systematic real-world testing and evaluation. Such measures are essential for gauging models' practical impact and fostering ethical AI that ensures fairness and equity in healthcare.
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