Multilayer perceptron based network to identify baseline illness risk
US11475302B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 6, 2020 |
| Grant date | Oct 18, 2022 |
| Priority date | — |
| Expiry date | Apr 14, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/30
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for training a baseline risk model, including: pre-processing input data by normalizing continuous variable inputs and producing one-hot input features for categorical variables; providing definitions for clean input data and dirty input data based upon various input data related to a patient condition; segmenting the input data into clean input data and dirty input data, wherein the clean input data includes a first subset and a second subset, where the first subset and the second subset include all of the clean input data and are disjoint; training a machine learning model using the first subset of the clean data; and evaluating the performance of the trained machine learning model using the second subset of the clean input data and the dirty input data.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.