ybyangjing/clops-nature-

PyTorch code for continual learning of cardiac signals with CLOPS

Continual Learning of Networks with CLOPS

CLOPS is a framework that allows neural networks to continually learn from clinical data streaming in over time.

This repository contains the PyTorch implementation of CLOPS. For details, see A clinical deep learning framework for continually learning from cardiac signals across diseases, time, modalities, and institutions. [Nature Communications Paper], [blogpost]

Requirements

The CLOPS code requires the following:

• Python 3.6 or higher
• PyTorch 1.0 or higher

Datasets

Download

The datasets can be downloaded from the following links:

1. PhysioNet 2020
2. Chapman
3. Cardiology

Pre-processing

In order to pre-process the datasets appropriately for CLOPS, please refer to the following repository

Training

To train the model(s) in the paper, run this command:

python run_experiments.py

Evaluation

To evaluate the model(s) in the paper, run this command:

python run_experiments.py