Methods and systems for predicting arrhythmia risk utilizing machine learning models
US12257060B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 17, 2021 |
| Grant date | Mar 25, 2025 |
| Priority date | — |
| Expiry date | May 24, 2043 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61B5/746
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
A system and method for determining an arrhythmia risk are provided and include memory to store specific executable instructions and a machine learning (ML) model trained to predict an arrhythmia with a characteristic of interest (COI) that exhibits a non-physiologic behavior. One or more processors are configured to execute the specific executable instructions to obtain CA signals collected by an implantable medical device (IMD), wherein the COI exhibits a physiologic behavior and apply the ML model to the CA signals to identify a risk factor that a patient will experience the arrhythmia at a future point in time even though the COI in the CA signals, exhibits a physiologic behavior.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.