QTc as Predictor of Cardiac Autonomy Function in Type-2 Diabetic Patient Using Neural Network

Abstract

The Cardiac autonomic neuropathy is a major issue in patients diagnosed with diabetes. Prolonged QTc is inclined to ventricular arrhythmia and sudden cardiac arrest. QTc prolongation shows a positive relationship with a degree of cardiac autonomic neuropathy in diabetic patients. This study intends to make a prediction based on the consecutive QTc prolongation of diabetic patients based on their ECG report taken in 3-5 years. A good prediction of the model designed with the help of the input and output data has been obtained with the help of an artificial neural network. The least mean square error can give us the best prediction result of our targeted output data.