2017 № 4 Experience of the Development of the Software Package for Neural Network Diagnosis and Prediction of Diseases of Hepatopancreatoduodenal Zone
The article presents the experience of the internal development of a software package for diagnosis and forecasting diseases of hepatopancreatoduodenal zone based on the artificial neural network of multilayer perceptron type with hyperbol- ic tangent taken as an activation function. The article includes the characteristics of the analyzed data which is the set of risk factors for the development of peptic ulcer, cholecystitis and pancreatitis and substantiates the necessity for the application of automated control systems acting on the principles of artificial neural networks. The methods of operating of a multilayer per- ceptron are given, and there are proposed modifications intended to optimize the development of the software package and to solve a number of problems that arise during practical implementation of the system and during data preparation. A set of possible input and output parameters of the network, intended for its training, is proposed. The article contains the description of the practically developed user interface, intended to create, configure, train and clinically apply the artificial neural network, as well as to construct its graphs and statistically control its functioning.
2018 № 4 Black box problem overcoming in medical applications of machine learning
A new interface for machine learning predicting models is proposed. Approach is based on optimal valid partitioning (OVP) technique and the modified method of statistically weighted syndromes (LSWR). The interface allows you to overcome the problem of “black box” illustrating prediction process by scatter plots, ROC curves and informative indicators ranking