Architecture for machine learning model to leverage hierarchical semantics between medical concepts in dictionaries
US11257592B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 26, 2019 |
| Grant date | Feb 22, 2022 |
| Priority date | — |
| Expiry date | Oct 19, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H10/60
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, a system, and a computer program product are provided. A machine learning model is generated to process adverse event information and produce multiple corresponding medical codes associated with the adverse event information, wherein the multiple medical codes are semantically and hierarchically related in a medical taxonomy. The machine learning model includes multiple parallel output layers, each of which is associated with a corresponding medical code. The machine learning model is trained with training data elements, each of which includes adverse event information mapped to respective multiple medical codes, wherein results from each of the output layers adjusts the machine learning model. After completing the training, information pertaining to an adverse event is applied to the machine learning model to determine the corresponding multiple medical codes within the medical taxonomy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.