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Prediction of fetal blood pressure during labour with deep learning techniques

Abstract:

Our objective is to develop a model for the prediction of minimum fetal blood pressure (FBP) during fetal heart rate (FHR) decelerations. Experimental data from umbilical occlusions in near-term fetal sheep (2698 occlusions from 57 near-term lambs) were used to train a convolutional neural network. This model was then used to estimate FBP for decelerations extracted from the final 90 min of 53,445 human FHR signals collected using cardiotocography. Minimum sheep FBP was predicted with a mean ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.3390/bioengineering10070775

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Institution:
University of Oxford
Division:
MSD
Department:
Women's & Reproductive Health
Research group:
Oxford Labour Monitoring Group
Role:
Author
More by this author
Role:
Author
ORCID:
0000-0002-8937-0846
More by this author
Role:
Author
ORCID:
0000-0003-0656-7035
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Women's & Reproductive Health
Research group:
Oxford Labour Monitoring Group; Big Data Institute
Role:
Author
Publisher:
MDPI
Journal:
Bioengineering More from this journal
Volume:
10
Issue:
7
Article number:
775
Publication date:
2023-06-28
Acceptance date:
2023-06-24
DOI:
EISSN:
2306-5354
Language:
English
Keywords:
Subjects:
Pubs id:
1494021
Local pid:
pubs:1494021
Deposit date:
2023-07-19

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