Learning and applying contextual similiarities between entities
US11875277B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 17, 2021 |
| Grant date | Jan 16, 2024 |
| Priority date | — |
| Expiry date | Mar 23, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/70
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Techniques disclosed herein relate to learning and applying contextual patient similarities. Multiple template similarity functions (118) may be provided (602). Each template similarity function may compare a respective subset of features of a query entity feature vector with a corresponding subset of features of a candidate entity feature vector. A composite similarity function (120) may be provided (604) as a weighted combination of respective outputs of the template similarity functions. A plurality of labeled entity vectors may be provided (606) as context training data. An approximation function may be applied (608) to approximate a first context label for each respective labeled entity vector. A first context specific composite similarity function may be trained (610) based on the composite similarity function by learning first context weights for the template similarity functions using a first loss function based on output of application of the approximation function to the first context training data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.