PREDICTING THE FUNCTIONAL RESULT OF TYMPANOPLASTY WITH THE AID OF NEURONAL NETWORKS USING A REDUCED DATA SET

Applications of artificial intelligence have made their presence felt over the last few years in many areas, including medicine. Since medicine is a field of high unpredictability, traditional methods of medical statistics are insufficient. Artificial intelligence applications, such as artificial neural networks, fuzzy logic, or genetic algorithm, allow intelligent models to predict the patient's response to treatment or to determine the risk to which the patient is exposed for a particular pathology. Our study aims to present a model of artificial neural networks to predict the functional outcome after surgery on the tympanic membrane (tympanoplasty). The methodology applied in this research is based on a reduced set of input data, one / two entries in the input layer and multiple outputs to the output layer.