The project traverses the intersection of maching learning and cardiology, utilizing a diverse array of algorithms and models to decipher complex patterns within electrocardiogram (ECG) data. The central focus lies on developing innovative computational frameworks capable of accurately identifying and classifying various types, thereby enabling prompt diagnosis and personalized treatment strategies.
Seidulla, Beksultan, "Leveraging Machine Learning for Cardiac Arrhythmia Insights" (2023). English Language Institute. 231.
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