2020 № 2 Legal problems of telemedicine technologies application in the context of fighting the spread of COVID-19 coronavirus
The purpose of the research is to analyze the legal problems of using telemedicine technologies, taking into account the experience of other countries; to assess the limitations of using telemedicine technologies in preventing the spread of COVID-19 coronavirus; to develop approaches to overcome existing restrictions in this area.
The authors consider the system of legal relations that arise between various participants in the provision of telemedicine services, focusing on international experience in this field.
On the example of the Russian Federation, the analysis of legal restrictions for the development of telemedicine technologies, which are typical for other countries, is carried out. A number of common problems of implementing telemedicine technologies are identified, as well as the specifics of legal regulation of telemedicine services in the Russian Federation.
Measures are proposed to overcome a number of legal restrictions in the use of telemedicine services related to licensing, labor legislation, etc.
2020 № 3 Making diagnostic decisions with the help of neural networks for disorders of the functioning of the gastrointestinal tract caused by the influence of parasites
The possibilities of using the processing and analysis method in medical research using an artificial neural network to improve the accuracy of diagnosing diseases of the gastrointestinal tract due to the influence of various parasites are considered.
Symptoms and diseases associated with the influence of the main parasites in the gastrointestinal tract are highlighted. Based on
this information, the implementation on the NeuroPro network emulator is carried out. The results of disease progression based
on selected symptoms using a neural network are presented. For a specific disease, significant input parameters of the network
2020 № 1 Decision support services for the diagnosis and treatment of diseases and their practical application on the example of ckd 5d
The article clarifies the concept of DSS, shows the trend of development of new services in medicine. The article
describes the developed DSS‑service for issuing recommendations for the treatment and diagnostic process on the example of
complications in patients on permanent hemodialysis, in particular, correction of anemia. The information and logical architecture
of the service, the rating and trigger models used, the underlying knowledge base, and their relationship are described.
Based on the theory of decision-making, the principle of making recommendations is shown. Examples of integration of the
service with various information systems and other data sources are given. The analysis of the results of the implementation
of the DSS service for the correction of anemia in patients with CKD5D in the Nephrology and hemodialysis departments of
the medical clinical company Nefrosovet in integration with the information and analytical system for managing treatment and
diagnostic processes Maximus.
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.