Methods and systems are provided for automatically diagnosing an electrocardiogram (ECG) using a hybrid system comprising a rule-based system and one or more deep neural networks. In one embodiment, by mapping ECG data to a plurality of features using a convolutional neural network, mapping the plurality of features to a preliminary diagnosis using a decision network, and determining a diagnosis based on the ECG data and the preliminary diagnosis using the rule-based system, a more accurate diagnosis may be determined. In another example, by incorporating both a rule-based system and one or more deep neural networks into the hybrid system, the hybrid system may be more easily adapted for use in various contexts/communities, as the one or more deep learning networks may be trained using context/community specific ECG data.
SYSTEMS AND METHODS FOR ELECTROCARDIOGRAM DIAGNOSIS USING DEEP NEURAL NETWORKS AND RULE-BASED SYSTEMS