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Anomaly detection is a common problem that is applied to machine learning/deep learning research. Here we will apply an LSTM autoencoder (AE) to identify ECG anomaly detections. In our experiments, anomaly detection problem is a rare-event classification problem. Therefore we will train our LSTM AE with major class, then we would have a higher mean squared error when model sees a minor class in the dataset.