Robust deep AUC/AUPRC maximization: a new surrogate loss and empirical studies on medical image classification
US12190505B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 2, 2021 |
| Grant date | Jan 7, 2025 |
| Priority date | — |
| Expiry date | Feb 21, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/03
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computer-based automated method of performing classification includes learning a deep neural network by maximizing an area under a receiver operating characteristic curve (AUC) or precision-recall curve (AUPRC) score wherein a margin-based surrogate loss function is applied, receiving an input into a deep neural network, and processing the input to the deep neural network to generate a prediction, wherein the prediction comprises a classification of the input. The computer-based automated method may be performed by executing instructions in at least one processor, and wherein said instructions are stored on a non-transitory memory readable by the at least one processor.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.