Invention Grant
- Patent Title: Technology to automatically identify the most relevant health failure risk factors
-
Application No.: US17192237Application Date: 2021-03-04
-
Publication No.: US11996201B2Publication Date: 2024-05-28
- Inventor: Divine E. Ediebah , Hajime Kusano , Ciaran A. Byrne , Krishnankutty Sudhir , Nick West
- Applicant: Abbott Laboratories
- Applicant Address: US IL Abbott Park
- Assignee: ABBOTT LABORATORIES
- Current Assignee: ABBOTT LABORATORIES
- Current Assignee Address: US IL Abbott Park
- Agency: Foley & Lardner LLP
- Main IPC: G16H50/30
- IPC: G16H50/30 ; G16H50/20

Abstract:
Systems, apparatuses and methods may provide technology that identifies minority class data and majority class data in patient-level data, wherein the minority class data corresponds to patients with a health failure and the majority class data corresponds to patients without the health failure, oversamples the minority class data to obtain synthetic class data and automatically reduces, via a machine learning classifier, a set of risk factor variables based on the majority class data, the minority class data and the synthetic class data.
Public/Granted literature
- US20220285028A1 TECHNOLOGY TO AUTOMATICALLY IDENTIFY THE MOST RELEVANT HEALTH FAILURE RISK FACTORS Public/Granted day:2022-09-08
Information query