Purpose. To determine the characteristics of changes in a person’s functional state under the influence of external factors and classify the severity of the patient’s condition by analyzing heart rate variability (HRV) indicators and expert characteristics
Specifications. The information technology was developed using the procedure of the Data Miner module of the STATISTICA 10 package. Data Mining algorithms were implanted into Weka, RapidMiner, SAS Enterprise Miner software, and a modern design tool was used – Python, R.
Application area. Medicine, healthcare. Healthcare institutions of Ukraine at different levels.
Advantages. According to experts, the use of the proposed IT for determining disease activity based on ECG indicators increases the sensitivity and accuracy of diagnosis and allows the doctor to identify the initial stages of the pathological process in an outpatient setting. The advantage of this approach is the possibility of simultaneous assessment of functional changes in the cardiovascular system and the level of disease activity even before clinical manifestations of the inflammatory process.
Technical and economic effect. The use of the developed IT to determine the functional state of operators, taking into account the type of autonomic regulation, allows us to assess the stressful nature of professional information loads using the components of the heart rate spectrum and identify significant psycho-emotional stress of operators for further psychophysiological adjustment. The use of the developed IT classification of the severity of patients allows us to assess the state of the cardiovascular system, determine markers of the stages of activity of this disease and build diagnostic rules, the use of which allows us to predict the severity of the disease in order to adjust the treatment tactics for patients.
Description. The created information technology for assessing pre-nosological and pathological conditions of a person combines three generalized stages: Stage I – filtering of primary indicators to reduce the volume under study; Stage II – creation and analysis of Data Mining models; Stage III – formation of final characteristics and classification of the human condition. The use of IT makes it possible to determine the features of changes in the functional state of people under the influence of external factors (in particular, information load) and classify the severity of the patient’s condition by analyzing heart rate variability indicators and expert characteristics of the condition under study.