Assessing risk of breast cancer recurrence
US11288795B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 21, 2019 |
| Grant date | Mar 29, 2022 |
| Priority date | — |
| Expiry date | Sep 23, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30096
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The subject disclosure presents systems and computer-implemented methods for assessing a risk of cancer recurrence in a patient based on a holistic integration of large amounts of prognostic information for said patient into a single comparative prognostic dataset. A risk classification system may be trained using the large amounts of information from a cohort of training slides from several patients, along with survival data for said patients. For example, a machine-learning-based binary classifier in the risk classification system may be trained using a set of granular image features computed from a plurality of slides corresponding to several cancer patients whose survival information is known and input into the system. The trained classifier may be used to classify image features from one or more test patients into a low-risk or high-risk group.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.