Translating ai algorithms from 12-lead clinical ECGS to portable and consumer ECGS with fewer leads

A computer program product, the computer program product comprising instructions stored on a non-transitory computer readable medium to cause at least one processor on a computer to:

• receive first electrocardiogram (ECG) data associated with a plurality of subjects and an electrocardiogram configuration including a predetermined set of leads and a time interval, the predetermined set of leads including a first number of leads, the first electrocardiogram data comprising, for each lead included in the predetermined set of leads, voltage data associated with at least a portion of the time interval,
• identify a first artificial intelligence model for a particular cardiac disease state;
• train the first artificial intelligence model on the first ECG data;
• receive second ECG data derived from a particular device, the second ECG data being associated with a second number of leads, the second number of leads being fewer leads than the first number;
• select, from the predetermined set of leads, a training lead that most closely resembles at least one lead of the particular device, at least in part by iteratively replacing data from one or more leads of the predetermined set of leads with ECG data associated with the second number of leads and evaluating performance of each iteration of the first artificial intelligence model;
• fine-tune the first artificial intelligence model by iteratively identifying one or more frozen layers and one or more unfrozen layers, freezing the one or more frozen layers, and retraining the unfrozen layers, wherein subsequent iterations comprise unfreezing upstream layers from a last frozen layer;
• train a second artificial intelligence model using a training dataset comprising ECG data including the predetermined set of leads, the second artificial intelligence model being configured to generate artificial ECG data corresponding to each lead of the predetermined set of leads based on the training lead;
• record a pairing of the particular device and the second artificial intelligence model to a database of a compatibility service;
• input the second ECG data into the trained second artificial intelligence model;
• translate, by the second artificial intelligence model, the second ECG data into artificial ECG data corresponding to the leads of the predetermined set of leads;
• and
• process, by the first artificial intelligence model, the artificial ECG data to generate one or more predictions regarding the particular cardiac disease state.