Open AccessMODELING AND MANAGING MEDICAL DATA
Author(s) -
E. V. Geger,
Irina Kozlova
Publication year - 2020
Publication title -
avtomatizaciâ i modelirovanie v proektirovanii i upravlenii
Language(s) - English
Resource type - Journals
eISSN - 2658-6436
pISSN - 2658-3488
DOI - 10.30987/2658-6436-2020-3-21-27
Subject(s) - medical diagnosis , computer science , binary number , data mining , data science , raw data , mathematics , medicine , arithmetic , pathology , programming language
The article describes a statistical method for analyzing medical data based on the comparison of binary samples. Processing data that is accumulated in transactional medical information systems, based on the analysis of binary samples, allows you to determine the indicators of laboratory research and diagnoses that are characteristic of harmful production factors. This will contribute to the development of digital technologies in healthcare, which will improve both diagnostics and treatment methods, as well as facilitate the adoption of competent management decisions.
The research results were converted to binary form by comparing them with the statistical norm interval. Diagnoses were considered initially as a binary variable. The samples obtained as a result of binarization for two groups, the first group includes people whose production activities contain harmful factors, and the second – those who do not have these factors, were compared with each other.
The initial group turned out to be heterogeneous in relation to the other group, so it was decided to conduct a further study based on the development and testing of methods for adjusting samples in order to achieve uniformity while maximizing the preservation of medical data used for analysis.