Attribution methodologies for neural networks designed for computer-aided diagnostic processes
US11288800B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 23, 2019 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Aug 23, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG09G2380/08
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Introduced here are diagnostic platforms able to attribute an output produced by a neural network to its input, as well as communicate the relationship between the output and input in a comprehensible manner. Neural networks are increasingly being used for critical tasks, such as detecting the presence/progression of medical conditions. Accordingly, the importance of explaining how these neural networks produce outputs has grown in importance. By explaining how outputs are produced by a neural network, a diagnostic platform can build trust with medical professionals responsible for interpreting the outputs, identify possible modes of neural network failure, and identify the latent variable(s) responsible for producing a given output.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.