A computer-implemented method of facilitating electrocardiogram ("ECG") analysis, the method comprising: receiving one or more sensed ECG traces for a patient, each of the sensed ECG traces representing sensed patient heart activity over a sensed time period; for each of the one or more sensed ECG traces: identifying a plurality of corresponding sensed ECG trace segments, each of the sensed ECG trace segments representing sensed patient heart activity for the patient over a segment of the sensed time period; and determining a representative ECG trace based on at least one of the identified corresponding sensed ECG trace segments; and causing at least one neural network classifier to be applied to the one or more determined representative ECG traces to determine one or more diagnostically relevant scores related to at least one diagnosis of the patient; characterized in that determining the representative ECG trace comprises identifying a subset of the plurality of corresponding sensed ECG trace segments, the subset excluding at least one of the plurality of corresponding sensed ECG trace segments, and determining the representative ECG trace based on the identified subset; and wherein identifying the subset of the plurality of corresponding sensed ECG trace segments comprises: applying principal component analysis to the plurality of corresponding sensed ECG trace segments to determine a respective set of principal component scores associated with each of the corresponding sensed ECG trace segments; and comparing the principal component scores to identify the at least one of the plurality of corresponding sensed ECG trace segments to be excluded from the subset. receiving one or more sensed ECG traces for a patient, each of the sensed ECG traces representing sensed patient heart activity over a sensed time period; for each of the one or more sensed ECG traces: identifying a plurality of corresponding sensed ECG trace segments, each of the sensed ECG trace segments representing sensed patient heart activity for the patient over a segment of the sensed time period; and determining a representative ECG trace based on at least one of the identified corresponding sensed ECG trace segments; and causing at least one neural network classifier to be applied to the one or more determined representative ECG traces to determine one or more diagnostically relevant scores related to at least one diagnosis of the patient; characterized in that determining the representative ECG trace comprises identifying a subset of the plurality of corresponding sensed ECG trace segments, the subset excluding at least one of the plurality of corresponding sensed ECG trace segments, and determining the representative ECG trace based on the identified subset; and wherein identifying the subset of the plurality of corresponding sensed ECG trace segments comprises: applying principal component analysis to the plurality of corresponding sensed ECG trace segments to determine a respective set of principal component scores associated with each of the corresponding sensed ECG trace segments; and comparing the principal component scores to identify the at least one of the plurality of corresponding sensed ECG trace segments to be excluded from the subset. identifying a plurality of corresponding sensed ECG trace segments, each of the sensed ECG trace segments representing sensed patient heart activity for the patient over a segment of the sensed time period; and determining a representative ECG trace based on at least one of the identified corresponding sensed ECG trace segments; and causing at least one neural network classifier to be applied to the one or more determined representative ECG traces to determine one or more diagnostically relevant scores related to at least one diagnosis of the patient; characterized in that determining the representative ECG trace comprises identifying a subset of the plurality of corresponding sensed ECG trace segments, the subset excluding at least one of the plurality of corresponding sensed ECG trace segments, and determining the representative ECG trace based on the identified subset; and wherein identifying the subset of the plurality of corresponding sensed ECG trace segments comprises: applying principal component analysis to the plurality of corresponding sensed ECG trace segments to determine a respective set of principal component scores associated with each of the corresponding sensed ECG trace segments; and comparing the principal component scores to identify the at least one of the plurality of corresponding sensed ECG trace segments to be excluded from the subset. applying principal component analysis to the plurality of corresponding sensed ECG trace segments to determine a respective set of principal component scores associated with each of the corresponding sensed ECG trace segments; and comparing the principal component scores to identify the at least one of the plurality of corresponding sensed ECG trace segments to be excluded from the subset.