Artificial neural networks in prediction of atrial fibrillation in men with coronary artery disease

Aim. The aim of the study was to select, based on mathematical apparatus of artificial neural networks (ANN), the most sensitive parameters for creating an ANN model aimed at prediction of atrial fibrillation (AF) in men with coronary artery disease (CAD).Material and Methods. The study focused on data of men from the register of coronary angiography with angiographically proven coronary artery disease: the main group comprised 180 men with AF; the comparison group comprised 713 men of comparable age without AF. The ANN mathematical model, a multilayer perceptron with one hidden layer, was used to assess the risk of AF. The initial group of patients was divided into three samples: the training, test, and control samples.Results. Patients with AF were significantly less likely to be employed in budget organizations (55.0% vs 63.7%, p = 0.040) and more often showed higher (III-IV) heart failure NYHA classes (49.2% vs 21.1%, p