Open AccessThe software complex for biochemical indicators monitoring taking into account ecological background of the region
Author(s) -
T. Y. Mamelina,
Anastasia V. Pushkareva,
V. E. Veipan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1889/3/032023
Subject(s) - computer science , disease , class (philosophy) , residence , set (abstract data type) , software , process (computing) , sample (material) , data set , machine learning , artificial intelligence , data mining , data science , medicine , pathology , demography , chemistry , chromatography , sociology , programming language , operating system
This article is devoted review the process of using new methods of hypertonic disease monitoring. The authors suggest to use patient’s immunological and biochemical homeostasis for predicting and diagnosis this disease. It is proved that these data can be used for monitoring and controlling patients. The correlation between immuno-biochemical parameters and the ecological background patient’s place of residence are set. The problem of the design and construction of specialized complex laboratory control based on client-server architecture is considered. For data analysis supposed to be used statistical and intellectual processing methods. For example, in article describes the basic classification algorithm called “k nearest neighbors”. When the size of “training sample” is sufficient the accuracy in determining the class label reaches 99%. In conclusion emphasizes the importance of developing methods for early diagnosis of cardiovascular disease and using the modern methods for data analysis.