Abstract
Intrapartum fetal surveillance for early detection of fetal acidosis in clinical practice focuses on reducing neonatal morbidity via early detection. It is the subject of on going research studies attempting notably to improve detection performance by reducing false positive rate. In that context, the present contribution tailors to fetal heart rate variability analysis a graph-based dimensionality reduction procedure performed on scattering coefficients. Applied to a high quality and well-documented database constituted by obstetricians from a French academic hospital, the low dimensional embedding enables to distinguish between the temporal dynamics of healthy and acidotic fetuses, as well as to achieve satisfactory detection performance detection compared to those obtained by the clinical-benchmark FIGO criteria.
| Original language | English |
|---|---|
| Title of host publication | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
| Pages | 6373-6376 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781424479290 |
| DOIs | |
| State | Published - 2 Nov 2014 |
| Externally published | Yes |
| Event | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 - Chicago, United States Duration: 26 Aug 2014 → 30 Aug 2014 |
Publication series
| Name | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
|---|
Conference
| Conference | 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 |
|---|---|
| Country/Territory | United States |
| City | Chicago |
| Period | 26/08/14 → 30/08/14 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Dimensionality reduction
- Embedding
- Intrapartum fetal heart rate variability
- Scattering transform
All Science Journal Classification (ASJC) codes
- Health Informatics
- Computer Science Applications
- Biomedical Engineering
- General Medicine
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