Automatically evaluating likely accuracy of event annotations in field data
US10114807B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 12, 2013 |
| Grant date | Oct 30, 2018 |
| Priority date | — |
| Expiry date | Feb 21, 2034 |
Classification
- Technology area (CPC A)Human Necessities
- CPC primaryA61N1/39044
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Embodiments operate in contexts where field data have been generated from a field event, and annotations have been generated from the field data, which purport to identify events within the field data, such as CPR compressions and ventilations. Metrics are generated from the annotations, which are used in training. In such contexts, a grade may be assigned that reflects how well the annotations meet one or more accuracy criteria. The grade may be used in a number of ways. Reviewers may opt to disregard field data and metrics that have a low grade. Expert annotators may be guided as to precisely which annotations to revise, saving time. A low grade may decide that the results are not emailed to reviewers, but to annotators. A learning medical device can use the grade internally to adjust its own internal parameters so as to improve its annotating algorithms.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.