Machine learning framework for detection of chronic health conditions
US12176109B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 10, 2022 |
| Grant date | Dec 24, 2024 |
| Priority date | — |
| Expiry date | Sep 25, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A system and method are disclosed for detecting chronic health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process the monitored parameter data collected by the wearable device as well as additional embedding data obtained from health records corresponding to a user account registered to the wearable device. In some examples, the input vector can also include embedding data related to social determinants data and/or demographic data. The output of the deep learning algorithms provides predictions that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.