Systems and methods for reduced lead electrocardiogram diagnosis using deep neural networks and rule-based systems
US11617528B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 8, 2019 |
| Grant date | Apr 4, 2023 |
| Priority date | — |
| Expiry date | May 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/20
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Methods and systems are provided for automatically diagnosing a patient based on a reduced lead electrocardiogram (ECG), using one or more deep neural networks. In one embodiment, a method for automatically diagnosing a patient using a reduced lead ECG comprises, acquiring reduced lead ECG data, wherein the reduced lead ECG data comprises less than twelve lead signals, determining a type of each of the less than twelve lead signals, selecting a deep neural network based on the type of each of the less than twelve lead signals, and mapping the less than twelve lead signals to a diagnosis using the deep neural network. In this way, reduced lead ECG data may be mapped to a diagnosis using an intelligently selected deep neural network, wherein the deep neural network was trained on reduced lead ECG data comprising a same set of ECG lead types as the acquired reduced lead ECG data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.