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Prediction of In-Hospital Cardiac Arrest in the Intensive Care Unit: Machine Learning-Based Multimodal Approach.

Hsin-Ying LeePo-Chih KuoFrank QianChien-Hung LiJiun-Ruey HuWan-Ting HsuHong-Jie JhouPo-Huang ChenCho-Hao LeeChin-Hua SuPo-Chun LiaoI-Ju WuChien-Chang Lee
Published in: JMIR medical informatics (2024)
Using only vital signs and information available in the electronic medical record, our model demonstrates it is possible to detect a trajectory of clinical deterioration up to 13 hours in advance. This predictive tool, which has undergone external validation, could forewarn and help clinicians identify patients in need of assessment to improve their overall prognosis.
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