Attention-based multiple instance learning
US12431245B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Apr 26, 2023 |
| Grant date | Sep 30, 2025 |
| Priority date | — |
| Expiry date | Feb 5, 2044 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V20/695
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods relate to predicting disease progression by processing digital pathology images using neural networks. A digital pathology image that depicts a specimen stained with one or more stains is accessed. The specimen may have been collected from a subject. A set of patches are defined for the digital pathology image. Each patch of the set of patches depicts a portion of the digital pathology image. For each patch of the set of patches and using an attention-score neural network, an attention score is generated. The attention-score neural network may have been trained using a loss function that penalized attention-score variability across patches in training digital pathology images labeled to indicate no or low subsequent disease progression. Using a result-prediction neural network and the attention scores, a result is generated that represents a prediction of whether or an extent to which a disease of the subject will progress.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.