Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data

This article describes the development and validation of an AI model for predicting mortality in critically ill patients. The use of multimodal data and multicenter data suggests a robust approach. The focus on external validation is crucial for assessing the model's generalizability. The research likely aims to improve patient care by enabling earlier interventions.

• •Focuses on predicting mortality in critically ill patients.
• •Employs a multimodal AI model.
• •Utilizes multicenter data for development and validation.
• •Emphasizes external validation for generalizability.