International Business Machines Corporation
Identifying and indexing discriminative features for disease progression in observational data

Last updated:

Abstract:

A system (or method) for generation and employment of disease progression model(s) that facilitates identifying and indexing discriminative features for disease progression in observational data. The disease progression prediction system comprises a processor that executes computer executable components stored in memory. A receiving component receives and learns observational patient data. A model generation component builds a preliminary disease progression model. An identification component identifies discriminative clinical features for different disease stages. A ranking component ranks discriminative powers of clinical features for respective pairs of disease stages; wherein the model generation component employs the ranked features to generate a final disease progression model.

Status:
Grant
Type:

Utility

Filling date:

31 Oct 2017

Issue date:

16 Nov 2021