Scilight Press

Early detection of any abnormalities can give further insights into the pregnancy and will provide more time to parents and doctors to prepare for these unnatural circumstances. Cardiotocography (CTG) is a technique used for monitoring fetal heart rate. It is widely used to ensure fetal well-being during pregnancies at high risk. Use of machine-learning techniques automated this task and reduced the chances of diagnostic errors. Deep learning also has powerful algorithms for learning complicated characteristics and higher-level semantics. The principal objective of this paper was to dissect the boundaries of different classification algorithms and contrast their prescient exactnesses to discover the best classifier for ordering fetal well-being.