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Diagnostic prediction for resting ECG. A 12 lead ECG (left) is transformed by a convolutional neural network (center) into prediction probabilities for 76 different labels (high probabilities in blue, low ones in white). The predicted diagnosis is composed of all labels with probability higher than a given threshold (0.5 here). From this predicted diagnosis a binary outcome is calculated according to what is being studied (e.g. AF/no AF, AD/no AD).
