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EjectionFractionPrediction

Ejection Fraction Prediction model without requiring segmentation, achieving MAE of 4.12% using labelled EchoNet-Dynamic data and unlabelled EchoNet-Pediatric data.

EjectionFractionPrediction and its dependencies can be installed by navigating to the cloned directory and running

pip install --user .

Running the model

The model can be run by navigating to the cloned directory and running

efpredict predict

You will need to request access to the EchoNet-Dynamic dataset by completing the form on this page: https://echonet.github.io/dynamic/index.html#access You will need to request access to the EchoNet-Pediatric dataset by completing the form on this page: https://echonet.github.io/lvh/index.html#access You will need to request access to the EchoNet-LVH (Not essential) dataset by completing the form on this page: https://echonet.github.io/pediatric/index.html#access

Once you have access to the data, download it and write the path of the EchoNet datasets in the efpredict.cfg file.

Some shuffling of data is required to run the model, namely in EchoNet-Pediatric.

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Ejection Fraction Prediction model without requiring segmentation.

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