The association between fetal intracranial hemorrhages detected on MRI and neurodevelopment.

Purpose: Fetal intracranial hemorrhage is rarely identified in prenatal imaging. When identified, sparse data regarding neurodevelopmental outcomes worsens prenatal dilemmas. This MRI-based study aimed to assess prenatal characteristics and neurodevelopmental outcomes of fetal intracranial hemorrhage.

Utilization of machine-learning models to accurately predict the risk for critical COVID-19.

Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk for deterioration during their hospital stay is essential for effective patient allocation and management. To predict patient risk for critical COVID-19 based on status at admission using machine-learning models. Retrospective study based on a database of tertiary medical center with designated departments for patients with COVID-19.