SYSTEMS AND METHODS TO PROCESS ELECTRONIC IMAGES TO PREDICT PROGRESSION AND REGRESSION

Original (Chinese)

A computer-implemented method for predicting cardiovascular disease risk, the method including: receiving a first patient history data comprising imaging data and/or non-imaging data for a patient at a first time point; selecting prediction report parameters defining a type of cardiovascular event and a risk prediction time scale; processing the first patient history data using a trained machine learning model configured to predict disease onset, progression, and/or regression over time, wherein the trained machine learning model is trained using patient subsets created based on patient history characteristics and outcomes; generating a risk prediction for the selected type of cardiovascular event over the selected risk prediction time scale based on the processed first patient history data; generating a risk prediction report based on the risk prediction; and outputting the risk prediction report.