Few-Shot Learning and Machine-Learned Model for Disease Classification

A method for machine training for disease classification, the method comprising:

• identifying an anatomical or functional characteristic linked to a pathology;
• locating data samples of patient data having known values of the anatomical and/or functional characteristics;
• machine training a first classifier with the data samples as training data where the known values are ground truth, the first classifier machine trained to output the anatomical or functional characteristic;
• machine training a second classifier adapted from the machine-trained first classifier, the second classifier machine trained with few-shot learning to output the pathology;
• and
• storing the machine-trained second classifier.

A medical imaging system for cardiac classification, the medical imaging system comprising:

• a medical imager configured to scan a patient;
• an image processor configured to classify a cardiac condition of the patient from output of a few-shot machine-trained model adapted from a multi-task trained initial model where multiple tasks of the multi-task trained initial model are anatomical and/or functional characteristics linked to the cardiac condition;
• and
• a display configured to display information derived from the cardiac condition.