System development of the clinical data analysis of patients with diabetes for assistance in creating therapy and estimating efficiency of its application

International Scientific Conference «AGRITECH-2019: Agribusiness, Environmental Engineering and Biotechnologies»

农业科学;生态环境科学;生物科学

Sirotinin, A.A.^1 ; Popov, A.A.^1 ; Dorrer, M.G.^1^2

Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av. 31, Krasnoyarsk

660037, Russia^1

Siberian Federal University, 79 Svobodny pr., Krasnoyarsk

660041, Russia^2

关键词: Assistance system;    Clinical data analysis;    Data and information;    Effectiveness measure;    ITS applications;    Neural network method;    Personal information;    System development;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/315/3/032009/pdf
DOI  :  10.1088/1755-1315/315/3/032009

来源: IOP

【 摘 要 】

The article analyzes data on the methods of treating patients with diabetes, as well as the possibility of obtaining additional information based on the processing of case histories by neural network methods, which is later used to build a decision-making assistance system for medical specialists. This information system can be used to assess the risks arising in the treatment of patients, allows you to more accurately set the diagnosis, prescribe treatment and monitoring dynamics of the effectiveness measures taken in relation to the patient. Presents solutions related tasks to data collection, processing and normalization both in the form of human analysis and with the help of machine learning systems. Affected by the heterogeneity of medical data. An analysis is made of existing systems with the same desired result in decision making for the medical sector. The approaches to the practical implementation with the observance of the norms and rules for handling personal information are considered. Accurately described the desired target result in achieving the solution of the task that satisfies a number of requirements of specialists using a similar system on their existing clinical data. The most important part of the system is the implementation of an adaptive method that allows specialists to influence the operation of the system by using the data and information at their disposal that is specific to a given region and social standard of living. Further possibilities for the application and development of technology in the future by adding additional methods to the already created system, affecting the efficiency of its work, as well as the possibility of creation new methods.