Application of bayesian networks to patient screening and treatment
US11562323B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 30, 2010 |
| Grant date | Jan 24, 2023 |
| Priority date | — |
| Expiry date | Nov 20, 2030 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16Z99/00
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
According to one aspect of the invention, health insurance claim data for a first group of individuals is obtained to generate a training corpus, including a training set of claim data and a holdout set of claim data. The first group of individuals represents enrollees of one or more first health insurance plans and the health insurance claim data represents historic insurance claim information for each individual in the first group. A Bayesian belief network (BBN) model is created by training a BBN network based on the training set of claim data using predetermined machine learning algorithms. The BBN model is validated using the holdout set of claim data. The BBN model, when having been successfully validated, is configured to identify at least one of individuals with risk for a disorder and individuals with risk who are most likely to benefit from intervention and treatment for the disorder.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.