(3.239.95.36)
[ij] [ij] [ij] 
Email id
 

Indian Journal of Public Health Research & Development
Year : 2019, Volume : 10, Issue : 8
First page : ( 651) Last page : ( 657)
Print ISSN : 0976-0245. Online ISSN : 0976-5506.
Article DOI : 10.5958/0976-5506.2019.01961.2

Cardiotocography Class Status Prediction Using Machine Learning Techniques

Appaji Sangapu Venkata1, Shankar R Shiva2, Murthy K. V. S.2, Rao Chinta Someswara2

1Assistant Professor, Department of CSE, KKR & KSR Institute of Technology and Sciences, Guntur, A.P, India

2Assistant Professor, Department of CSE, S.R.K.R Engineering College, Bhimavaram, W.G. District, A.P. India

Online published on 26 September, 2019.

Abstract

Physicians used Cardiotocography (CTG) to knowing of fetal well-being and potential complications from pregnant women. They used a continuous electronic record of the baby's heart rate took from the mother's abdomen. They visualized the unhealthiness that will give an opportunity for early intervention. CTG class status is classified in this paper with machine learning methods by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals and visualized the acquired information. This classification and visualization will help the doctor while treatment the patient. Experimental results has shown good accuracy score and low error rate.

Top

Keywords

Cardiotocography, classification, machine learning, data mining, uterine contraction, fetal heart rate.

Top

 
║ Site map ║ Privacy Policy ║ Copyright ║ Terms & Conditions ║ Page Rank Tool
753,998,321 visitor(s) since 30th May, 2005.
All rights reserved. Site designed and maintained by DIVA ENTERPRISES PVT. LTD..
Note: Please use Internet Explorer (6.0 or above). Some functionalities may not work in other browsers.