Prediction of prognosis in patients with tetralogy of Fallot based on deep learning imaging analysis.

Gerhard-Paul Diller Stefan OrwatJulius VahleUlrike M M BauerAleksandra UrbanSamir SarikouchFelix BergerPhilipp BeerbaumHelmut Baumgartnernull null

Published in: Heart (British Cardiac Society) (2020)

We present data on the utility of machine learning algorithms trained on external imaging datasets to automatically estimate prognosis in patients with ToF. Due to the automated analysis process these two-dimensional-based algorithms may serve as surrogates for labour-intensive manually attained imaging parameters in patients with ToF.

Keyphrases

machine learning
deep learning
high resolution
artificial intelligence
mass spectrometry
big data
convolutional neural network
electronic health record
high throughput
fluorescence imaging