Classification Algorithm and its Application for Prognosis of the Relapses for Papillary Microcarcinoma of the Thyroid Gland According to the Data of a Preoperative Examination
摘要
Abstract
The article presents the main ideas and capabilities for teaching classification with the FRAGMENT teacher algorithm, which allows you to find an ensemble of classifying solvers, and the POTENTIAL classification algorithm (decision-making), in which voting on a set of ensembles of solvers is carried out. The paper presents the results of the use of the programs FRAGMENT and POTENTIAL for the prognosis of relapse after surgery for papillary thyroid microcarcinoma according to the data of a preoperative examination. The possibility of relapse is the most significant result of the long-term consequences of surgery. The results indicate the prospects of using the developed methods to predict relapse.