alexa Artificial Neural Network System in the Automated Diagnosis of Fetal Heart Rate | OMICS International | Abstract
ISSN: 2157-7420

Journal of Health & Medical Informatics
Open Access

Like us on:

OMICS International organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)

Research Article

Artificial Neural Network System in the Automated Diagnosis of Fetal Heart Rate

K Meda1*, Y Noguchi2, F Matsumoto2 and T Nagasawa3

1Department of Obstetrics and Gynecology (emeritus) of Tottori University Medical School, Yonago, Japan

2Department of applied physics, National Defense Academy, Yokosuka, Japan

3Department of Information Technology, TOITU Ltd, Tokyo, Japan

*Corresponding Author:
Kazuo Maeda
Department of Obstetrics and Gynecology
Tottori University Medical School
3-125, Nadamachi, Yonago, Tottoriken, 683-0835 Japan
Tel: 81-859-22-6856
E-mail: [email protected]

Received date: December 08, 2011; Accepted date: January 05, 2012; Published date: January 14, 2012

Citation: Meda K, Noguchi Y, Matsumoto F, Nagasawa T (2012) Artificial Neural Network System in the Automated Diagnosis of Fetal Heart Rate. J Health Med Informat S5:001. doi: 10.4172/2157-7420.S5-001

Copyright: © 2012 Meda K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Fetal heart rate (FHR) tracing with uterine contraction is the most commonly utilized for fetal monitoring during pregnancy and in the labor. Automated computerized diagnosis of FHR was intended and recently introduced artificial neural network analysis because of its very objective nature. FHR tracing was quantified and FHR score was obtained, FHR frequency power spectrum was analyzed to diagnose sinusoidal FHR to apply in artificial neural network analysis. The neural network was composed of a soft ware with three layers associated with back-propagation system, and it was trained with 8 FHR parameters including the sinusoidal FHR for 10,000 times to obtain 100 % correct internal check. Trained network soft ware was copied with new computer to diagnose new subjects. Diagnostic input was the 8 FHR parameters of 3 periods of 5 min, and output was probabilities to be normal, intermediate and pathologic outcomes in percentage, of which diagnosis was correct in the comparison to simultaneously calculated FHR score that was high in pathologic outcome probability, moderate in intermediate and low in normal outcome probability. Neural network index derived from pathologic and normal outcome probabilities was useful in the outcome prediction of prolonged fetal monitoring

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

+1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version
Leave Your Message 24x7