/System And Methods For Generating And Leveraging A Disease-agnostic Model To Predict Chronic Disease Onset
Abstract

Methods, systems, and computer-readable media are disclosed herein for generating a disease-agnostic data model that can be used to predict the onset of multiple chronic diseases in individual patients. In an aspect, the data model is made by autonomously selecting features from longitudinal medical records of patients having chronic diseases that will become predictors for the onset of a chronic disease. The features are vectorized around a disease onset date and processed through a recurrent neural network to produce the data model. Then, the data model may leveraged to predict, for new longitudinal medical records that are input, a future time period when another patient is predicted to experience the onset of the chronic disease. The same data model may utilized to make predictions for multiple chronic diseases.

Full Text

What is claimed is:

Methods, systems, and computer-readable media are disclosed herein for generating a disease-agnostic data model that can be used to predict the onset of multiple chronic diseases in individual patients. In an aspect, the data model is made by autonomously selecting features from longitudinal medical records of patients having chronic diseases that will become predictors for the onset of a chronic disease. The features are vectorized around a disease onset date and processed through a recurrent neural network to produce the data model. Then, the data model may leveraged to predict, for new longitudinal medical records that are input, a future time period when another patient is predicted to experience the onset of the chronic disease. The same data model may utilized to make predictions for multiple chronic diseases.
Timeline
Filed
04/14/2026
Published
08/20/2026
Granted
Not Available
IPC Codes(2)
G16H 50/70:for mining of medical data, e.g. analysing previous cases of other patients
G16H 50/20:for computer-aided diagnosis, e.g. based on medical expert systems