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Background: Detecting kidney trauma on CT scans can be challenging and is sometimes overlooked. While deep learning (DL) has shown promise in medical imaging, its application to kidney injuries remains underexplored. This study aims to develop and validate a DL algorithm for detecting kidney trauma, using institutional trauma data and the Radiological Society of North America (RSNA) dataset for external validation.

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Importance: There are no validated decision rules for terminating resuscitation during in-hospital cardiac arrest. Decision rules may guide termination and prevent inappropriate early termination of resuscitation.

Objective: To develop and validate termination of resuscitation rules for in-hospital cardiac arrest.

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