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Code for: A hybrid method for heartbeat classification via convolutional neural networks, multilayer perceptrons and focal loss

Dataset

MIT-BIH Arrhythmia database

Usage

  • Reproduce the results

A pre-trained model is provided in the model directory. To reproduce our results, you should, first, download the MIT-BIH arrhythmia database from the above link and save it in the dataset directory. Then, execute preprocessing.py to obtain the training and test dataset. After that, just run pre-training.py and you will get the results of our paper.

  • Re-train the model

Just replace the last step of run pre-training.py with main.py.

Noted that the optimization function of Keras and TensorFlow is slightly different in different versions. Therefore, to reproduce our results, it suggests that using the same version of Keras and TensorFlow as us, in our work the version of Keras is 2.3.1 and TensorFlow is 1.15.0. In addition, Keras and TensorFlow have a certain randomness, the actual results may be somewhat floating.

Cite

If our work is helpful to you, please cite:

Wang T, Lu C, Yang M, et al. A hybrid method for heartbeat classification via convolutional neural networks, multilayer perceptrons and focal loss[J]. PeerJ Computer Science, 2020, 6: e324.

Email:

If you have any questions, please email to: wtustc@mail.ustc.edu.cn