Machine Learning Models for Fetal Health Classification Using Cardiotocography: Towards Improved Prenatal Care and Outcomes-Reference-Cited by-同舟云学术

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Machine Learning Models for Fetal Health Classification Using Cardiotocography: Towards Improved Prenatal Care and Outcomes

Published:2024-05-24 Issue: Volume:24 Page:1-6
ISSN:
Container-title:2024 5th International Conference for Emerging Technology (INCET)
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Author:

Goel Arnav¹,Sonowal Indra Ballav²,Saxena Vikram Kishore²,Bhukya Ramesh K.²

Affiliation:

1. Indian Institute of Information Technology Allahabad,Department of Information Technology,Prayagraj,Uttar Pradesh,India,211015

2. Indian Institute of Information Technology Allahabad,Department of Electronics and Communication Engineering,Prayagraj,Uttar Pradesh,India,211015

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592862/10592849/10592910.pdf?arnumber=10592910

Reference23 articles.

1. Perinatal Mortality in Sub-Saharan Africa: A Meta-Analysis of Demographic and Health Surveys

2. 3.6 Million Neonatal Deaths—What Is Progressing and What Is Not?

3. Quality of care for pregnant women and newborns—the WHO vision

4. Automatic Cardiotocography Diagnostic System Based on Hilbert Transform and Adaptive Threshold Technique

5. Has electronic fetal heart rate monitoring made a difference?

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