Machine learning extraction of clinical variable values for subjects from clinical record data
US12354720B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 20, 2023 |
| Grant date | Jul 8, 2025 |
| Priority date | — |
| Expiry date | Dec 20, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/048
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Described herein are techniques of using machine learning to automatically extract clinical variable values for subjects from clinical record data. The techniques designate certain clinical variables as hybrid variables that can be assigned values by machine learning model prediction. The techniques process, using a machine learning model trained to predict a value of a hybrid variable, clinical record data associated with a subject to obtain a predicted hybrid variable value and an associated confidence score. The techniques set the value of the hybrid variable for the subject to the predicted hybrid variable value when the model prediction is of sufficiently high confidence.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.