Title

Cardiotocography Class Status Prediction Using Machine Learning Techniques.

Authors

Appaji, Sangapu Venkata; Shankar, R. Shiva; Murthy, K. V. S.; Rao, Chinta Someswara

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.

Subjects

MACHINE learning; FETAL heart rate monitoring; FETAL heart rate; UTERINE contraction; HEART beat

Publication

Indian Journal of Public Health Research & Development, 2019, Vol 10, Issue 8, p651

ISSN

0976-0245

Publication type

Academic Journal

DOI

10.5958/0976-5506.2019.01961.2