Systems, devices, software, and methods for diagnosis of cardiac ischemia and coronary artery disease

A method for determining whether coronary artery occlusion is present in an individual, comprising:

• (i) positioning an electromagnetic field sensor within proximity to a chest of the individual, outside of a body of the individual, and not in contact with the body of the individual, wherein the electromagnetic field sensor is operably coupled to a sensing device comprising a processor and a non-transitory computer-readable storage medium encoded with software comprising a trained machine learning software module, wherein the trained machine learning software module is configured to generate a machine learning output classification indicative of a presence or absence of coronary artery occlusion in the individual, and wherein the trained machine learning software module is trained using training data comprising electromagnetic field measurements generated by a heart of each of a training set of individuals;
• (ii) using the electromagnetic field sensor to non-invasively sense an electromagnetic field measurement generated by the heart of the individual without administering a magnetically active agent to the individual;
• (iii) receiving, by the processor, the electromagnetic field measurement from the electromagnetic field sensor;
• (iv) analyzing the electromagnetic field measurement, using the processor and the trained machine learning software module;
• and
• (v) determining, using the processor and the trained machine learning software module, whether a coronary artery occlusion is present in the heart of the individual based on the machine learning output classification of the electromagnetic field measurement.