Interpretable deep learning framework for mining and predictive modeling of health care data
US11144825B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 1, 2017 |
| Grant date | Oct 12, 2021 |
| Priority date | — |
| Expiry date | Aug 12, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/70
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for creating an interpretable model for healthcare predictions includes training, by a deep learning processor, a neural network to predict health information by providing training data, including multiple combinations of measured or observed health metrics and corresponding medical results, to the neural network. The method also includes determining, by the deep learning processor and using the neural network, prediction data including predicted results for the measured or observed health metrics for each of the multiple combinations of the measured or observed health metrics based on the training data. The method also includes training, by the deep learning processor or a learning processor, an interpretable machine learning model to make similar predictions as the neural network by providing mimic data, including combinations of the measured or observed health metrics and corresponding predicted results of the prediction data, to the interpretable machine learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.