This study aims to establish an electronic medical record and imaging database for out-of-hospital cardiac arrest (OHCA) patients at NTUH Hsinchu Branch. Leveraging an AI deep learning model and an automated brain gray-white matter analysis system developed at NTUH, the research seeks to validate these tools externally. By integrating electronic medical records and brain imaging data, the project strives to enhance the accuracy of prognostic assessments, supporting physicians and families in decision-making for post-cardiac arrest care. Validation at Hsinchu Branch will assess the model's reliability across diverse medical settings and patient populations, optimizing its applicability and accuracy.
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Cerebral Performance Categories (CPC) Scale
Timeframe: From the time of ROSC achievement until hospital discharge or death, assessed up to 700 days