Code vector embeddings for similarity metrics
US10891352B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 21, 2018 |
| Grant date | Jan 12, 2021 |
| Priority date | — |
| Expiry date | Mar 27, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H10/60
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Aggregate vectors corresponding to non-textual information/data are provided in a multi-dimensional space. A computing entity access a plurality of instances of medical information comprising medical codes. The computing entity generates one or more medical sentences from the plurality of instances of medical information. Each medical sentence comprises one or more medical codes. The computing entity generates an embedding vector dictionary comprising a plurality of multi-dimensional vectors based on a medical embedding model trained using machine learning and the one or more medical sentences. Each multi-dimensional vector corresponds to a medical code. The computing entity generates a plurality of aggregate vectors based on the embedding vector dictionary and analyzes at least a portion of the plurality of aggregate vectors to identify two or more aggregate vectors that are similar or different based on a distance between the two or more aggregate vectors in the multi-dimensional space.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.