ECG classification and the "heart age" prediction using machine learning

Thesis

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Electrocardiogram (ECG) is an important clinical measurement of cardiac activity. The major challenge in incorporating ECG time-series into CVD risk metrics is extracting features and classifying the ECG time-series into appropriate ECG abnormality groups. Therefore we set out to use machine learning to address this challenge.

We used machine learning to analyse 12-lead, 500Hz, 10-s electrocardi...

Expand abstract

Authors: Shen, Y

• Type of award: DPhil
• Level of award: Doctoral
• Awarding institution: University of Oxford
• Language: English
• Keywords: LCN; layer-wise convex networks; deep learning; ECG; AutoNet
• Subjects: Machine learning