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DATA PROCESSING AND ANALYSIS
Algorithm of data filtration and dependencies searching in analysis of patients with sub-mild cognitive decline
N. N. Yakhnoab, V. N. Gridina, N. N. Koberskayaab, D. S. Smirnova, V. I. Solodovnikova a Design Information Technologies Center Russian Academy of Sciences (DITC RAS), Odintsovo, Moscow region
b I. M. Sechenov First Moscow State Medical University (Sechenov University)
Abstract:
Paper is aimed to develop algorithm for searching statically significant dependencies on medical data of patients with sub-mild cognitive decline. Algorithms and methods of statistical processing and transformation of medical data of patients are considered. A method for identifying groups of indicators that have the greatest consistency and separation capacity for a priori groups of patients and a method for selecting key observations are proposed. Combinatorial canonical analysis is applied to find the most important risk factors for cognitive decline. Confirmed the results of previous studies on the closest relationship between cognitive decline and cardiovascular risk factors such as arterial hypertension or myocardial infarction in anamnesis
Keywords:
dimension reduction, multivariate statistical methods, canonical analysis, cognitive decline.
Citation:
N. N. Yakhno, V. N. Gridin, N. N. Koberskaya, D. S. Smirnov, V. I. Solodovnikov, “Algorithm of data filtration and dependencies searching in analysis of patients with sub-mild cognitive decline”, Informatsionnye Tekhnologii i Vychslitel'nye Sistemy, 2021, no. 2, 34–43
Linking options:
https://www.mathnet.ru/eng/itvs726 https://www.mathnet.ru/eng/itvs/y2021/i2/p34
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Abstract page: | 52 | Full-text PDF : | 38 |
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