Method and system for predicting optimal epilepsy treatment regimes
US11315685B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 25, 2017 |
| Grant date | Apr 26, 2022 |
| Priority date | — |
| Expiry date | Jul 24, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H70/40
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
A method of building a machine learning pipeline for predicting the efficacy of anti-epilepsy drug treatment regimens is provided. The method includes providing electronic health records data; constructing a patient cohort from the electronic health records data by selecting patients based on a defined target variable indicating anti-epilepsy drug treatment regimen efficacy; constructing a set features found in or derived from the electronic health records data; electronically processing the patient cohort to identify a subset of the features that are predictive for anti-epilepsy drug treatment regimen efficacy for inclusion in predictive models configured for generating predictions representative of efficacy for a plurality of anti-epilepsy drug treatment regimens; and training the predictive computerized model to generate predictions representative of efficacy for a plurality of anti-epilepsy drug treatment regimens for the patients based on the defined target variable indicating anti-epilepsy drug treatment regimen efficacy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.