A Bio Inspired Approach for Cardiotocogram Data Classification

In health care industry, data mining plays a significant task for predicting diseases. Numeral number of tests must be requisite from the patient for detecting a disease. However, using data mining technique can reduce the number of test that are required. Cardiotocogram data are data used for survey of baby statement for pregnant women by recording baby's fetal heartbeats, and uterine contractions for women. This work proposes a supervised approach based on artificial bee colony to predict type of fetal statement of Cardiotocogram data using previous recorded data, which was proposed the first time by the authors in (Rahmani, 2016). This paper is a continuation of that work in order to validate the approach as meta-heuristic. The obtained results were very good and satisfactory.