Assessment of the Applicability of Machine Learning Methods for the Detection of Pathology of Internal Human Organs based on the Results of Bioelectrography

The possibility of using the bioelectrography method for detecting pathology of internal organs is considered. Sets of data sets for machine learning are formed on the basis of ultrasonic diagnostics readings. Machine learning methods were analyzed with an assessment of the feasibility of their use. The results of detection of pathology of internal organs with the use of classifiers are presented: Decision tree; KNN; Logistic regression; Random forest; SVC; XGBoost.