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Objective Patient information can be retrieved more efficiently in electronic medical record (EMR) systems by using machine learning models that predict which information a physician will seek in a clinical context. However, information-seeking behavior varies across EMR users. To explicitly account for this variability, we derived hierarchical models and compared their performance to non-hierarchical models in identifying relevant patient information in intensive care unit (ICU) cases.doi:10.1101/2020.09.18.20197434 fatcat:fm7k6pngj5drhks5rgkiygafiq