On an algorithm for decision-making for the optimization of disease prediction at the primary health care level using neural network clustering

Abstract

Background. A number of studies have been aimed at solving the problems of introducing information technology and systems, but the questions of informatization in rural medicine are not completely resolved. It is important to optimize the prognosis of diseases using available and inexpensive information methods for the improvement of primary healthcare. Objectives. The aim of our study was to develop an algorithm to optimize the decision-making prognosis of disease at the primary health care level based on information methods. Material and methods. The data used for analysis originated from the survey results of 63 patients with hypertension in educational and practical centers of primary health care (EPCPHC) of Ternopil region (Ukraine). For a deeper analysis and clustering, the neural network approach was used with the NeuroXL Classifier add-in application for Microsoft Excel. Results. Thirteen (19.40%) patients experienced health deterioration and the development of complications. It has been established that neural network clustering could effectively and objectively allocate patients to the appropriate category in terms of the average survey results. Cluster analysis results have shown that the combination of high blood pressure (systolic, diastolic and pulse) gave reason to anticipate the deterioration of patients' conditions. Conclusions. A decision algorithm was created in order to optimize the prediction of diseases at the primary health care level, and also to correct examination and treatment based on an analysis of average values of patients' examination and the use of neural network clustering.

Components of Oranta-AO software expert system for innovative application of blood pressure monitors

“…In Electrocardiography, methods of temporal and spectral analysis (Fourier transform) are used, in rheography—methods of morphological analysis, and in encephalography—methods of spectral analysis of the signal (Fourier transform). Since during the pressure measurement the body builds an adaptive response to shoulder compression and there are different types of reactions, the Hilbert–Huang transformation was additionally introduced to assess the body instantaneous adaptive reactions [ 1 – 4 , 11 – 14 , 24 – 28 ].…”

“…The analysis of the results obtained gave the authors an opportunity to develop and substantiate the methods of arterial oscillography for the first time. The obtained results are presented in the Thesis work of the doctor of biological sciences, monograph, methodical recommendations (approved by the Ministry of Health), 7 patents; 72 articles in journals [ 11 – 13 , 19 , 20 , 24 – 27 ]. Certification (EN 62304:2014, ISO 13485: 2018) in Ukraine is completed, PCT priority is completed.…”

“…Based on the methods and algorithms developed as a result of research, Oranta-AO software package was designed and developed, which allows the user to take measurements with an electronic blood pressure monitor, load them into the system, get calculated indicators, view them in a convenient way and see analytical information on the basis of which you can assess the state of the cardiovascular system and decide on further action [ 11 – 15 , 21 – 24 , 28 ].…”

“…In previous research concepts, substantiation, methods, algorithms, and tools of the new blood pressure monitor application were developed: The methods for the analysis of pulsations that occur in a pressure monitor cuff in response to shoulder (or other part of the body) compression under the influence of blood vessels pulse activity on compression or (and) decompression [ 17 , 19 , 28 ]. Selection and justification of the use of mathematical apparatus to solve problems for the methods implementation was made [ 17 , 19 , 24 , 28 ]. The software allowing the user to go through all the stages from direct measurement to full analysis of the results.…”

Ottawa Ankle Rules in primary care – awareness, importance and use by family physicians

“…Clinical decision rules enable physicians to make systematic and evidence-based clinical judgements [1][2][3]. The rate of application of these rules increases according to their academic acceptance, cost-effectiveness, simplicity and algorithmic structure [4].…”