Conference item
Fetal heart rate classification with convolutional neural networks and the effect of gap imputation on their performance
- Abstract:
-
Cardiotocography (CTG) is widely used to monitor fetal heart rate (FHR) during labor and assess the wellbeing of the baby. Visual interpretation of the CTG signals is challenging and computer-based methods have been developed to detect abnormal CTG patterns. More recently, data-driven approaches using deep learning methods have shown promising performance in CTG classification. However, gaps that occur due to signal noise and loss severely affect both visual and automated CTG interpretations,...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Bibliographic Details
- Publisher:
- Springer
- Host title:
- Machine Learning, Optimization, and Data Science
- Series:
- Lecture Notes in Computer Science
- Series number:
- 13810
- Pages:
- 459-469
- Place of publication:
- Cham, Switzerland
- Publication date:
- 2023-03-09
- Acceptance date:
- 2022-06-20
- Event title:
- 8th Annual Conference on Machine Learning, Optimization and Data science (LOD)
- Event location:
- Siena, Italy
- Event website:
- https://lod2022.icas.cc/
- Event start date:
- 2022-09-18
- Event end date:
- 2022-09-22
- DOI:
- EISSN:
-
1611-3349
- ISSN:
-
0302-9743
- EISBN:
- 9783031255991
- ISBN:
- 9783031255984
Item Description
- Language:
-
English
- Keywords:
- Pubs id:
-
1335966
- Local pid:
-
pubs:1335966
- Deposit date:
-
2023-06-29
Terms of use
- Copyright holder:
- Asfaw et al.
- Copyright date:
- 2023
- Rights statement:
- © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG.
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