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