Bayesian causal relationship network models for healthcare diagnosis and treatment based on patient data
US11734593B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 3, 2019 |
| Grant date | Aug 22, 2023 |
| Priority date | — |
| Expiry date | Aug 3, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/70
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Systems, methods, and computer-readable medium are provided for healthcare analysis. Data corresponding to a plurality of patients is received. The data is parsed to generate normalized data for a plurality of variables, with normalized data generated for more than one variable for each patient. A causal relationship network model is generated relating the plurality of variables based on the generated normalized data using a Bayesian network algorithm. The causal relationship network model includes variables related to a plurality of medical conditions or medical drugs. In another aspect, a selection of a medical condition or drug is received. A sub-network is determined from a causal relationship network model. The sub-network includes one or more variables associated with the selected medical condition or drug. One or more predictors for the selected medical condition or drug are identified.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.