Artificial Neural Networks Prognostic Evaluation of Post-Surgery Complications in Patients Underwent to Coronary Artery Bypass Graft Surgery

In this paper we explore the applications of artificial neural networks in the field of heart surgery, more specifically in the prognostic evaluation of post-surgery complications, such as death, reintubation, prolonged mechanical ventilation and the need for extracorporeal circulation in patients who underwent coronary artery bypass graft surgery. Predictive variables were limited to information available before the procedure, and outcome variables were represented only by events that occurred postoperatively. We also employed the principal component analysis technique to further reduce the complexity of our input data set in an attempt to improve artificial neural network efficiency and reliability.