A deep learning mixed-data type approach for the classification of FHR signals
The Cardiotocography (CTG) is a widely diffused monitoring practice, used in Ob-Gyn Clinic to assess the fetal well-being through the analysis of the Fetal Heart Rate (FHR) and the Uterine contraction signals. Due to the complex dynamics regulating the Fetal Heart Rate, a reliable visual interpretat...
Main Authors: | Edoardo Spairani, Beniamino Daniele, Maria Gabriella Signorini, Giovanni Magenes |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-08-01
|
Series: | Frontiers in Bioengineering and Biotechnology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fbioe.2022.887549/full |
Similar Items
-
Editorial: Biomedical engineering technologies and methods in antenatal medicine
by: Giovanni Magenes, et al.
Published: (2023-08-01) -
Data-Driven Insights into Labor Progression with Gaussian Processes
by: Tilekbek Zhoroev, et al.
Published: (2024-01-01) -
Hybrid-FHR: a multi-modal AI approach for automated fetal acidosis diagnosis
by: Zhidong Zhao, et al.
Published: (2024-01-01) -
Deep-Learning-Based Classification of Digitally Modulated Signals Using Capsule Networks and Cyclic Cumulants
by: John A. Snoap, et al.
Published: (2023-06-01) -
Deep learning in the classification and recognition of cardiac activity patterns
by: Łukasz Jeleń, et al.
Published: (2024-03-01)