Fetal Health Classification using AI from Cardiotocography Features-Reference-Cited by-同舟云学术

Fetal Health Classification using AI from Cardiotocography Features

Published:2023-12-21 Issue: Volume: Page:1544-1550
ISSN:
Container-title:2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA)
language:
Short-container-title:

Author:

Jyostna G¹,Goyal Himanshu Rai²,Soudagar Manzoore Elahi M.³,Parikh Swapnil⁴,Patil Harshal⁵,Alaskar Kamal⁶

Affiliation:

1. Potti Sriramulu Chalavadi Mallikarjuna Rao College of Engineering & Technology,Department of CSE-DS,Vijayawada,Andhra Pradesh,India,520 012

2. Graphic Era Deemed to be University,Department of Computer Science & Engineering,Dehradun,Uttarakhand,India,248002

3. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Department of VLSI Microelectronics,Chennai,Tamil Nadu,India,602105

4. Parul Institute of Engineering and Technology, Parul University, Post Limda,Department of Computer Science and Engineering,Waghodia,Gujarat,India,391760

5. Symbiosis International (Deemed University),Computer Science and Engineering, Symbiosis Institute of Technology,Pune,Maharashtra,India,412 115

6. BharatiVidyapeeth (Deemed To Be University), Institute of Management,Department of Computer Application,Kolhapur,Maharashtra,India,416003

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10424966/10425793/10426089.pdf?arnumber=10426089

Reference15 articles.

1. Neonatal and perinatal mortality: country, regional and global estimates;World Health Organization,2006

2. A review of fetal cardiac monitoring, with a focus on low- and middle-income countries

3. Digital signal extraction approach for cardiotocography image

4. Fetal Health State Detection Using Interval Type-2 Fuzzy Neural Networks

5. Early Diagnosis and Classification of Fetal Health Status from a Fetal Cardiotocography Dataset Using Ensemble Learning