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A Low-Power Wireless System for Predicting Early Signs of Sudden Cardiac Arrest Incorporating an Optimized CNN Model Implemented on NVIDIA Jetson
Article discusses the low survival rate of sudden cardiac arrest and its long-term risks that patients may experience. Authors propose a more effective method of recording and reporting sudden cardiac arrest symptoms so preventative measures may be instated earlier on to increase survival rate.
Date:
February 17, 2023
Creator:
Kota, Venkata Deepa; Sharma, Himanshu; Albert, Mark; Mahbub, Ifana; Mehta, Gayatri & Namuduri, Kamesh
System:
The UNT Digital Library