A person is considered as information-energy system with a host of feedbacks. The possibility of determining the statistical characteristics in a multiple intelligences profile of various social groups' representatives using the vibraimage technology is investigated. Theft and alcohol abuse have been chosen as examples of significant social problems including deviant behavior and the trigger of formation of various socially vulnerable groups. The comparative analysis of conscious and unconscious attitudes in multiple intelligences structure of individuals prone to deviant behavior and the control group allows differentiating professional preferences and the impact of society on different social groups.

The hypothesis of behavioral parameters dependence measured from person's head movements in quasi-stationary state on COVID-19 disease is discussed. Method for determining the dependence of vestibular-emotional reflex parameters on COVID-19, various diseases and pathologies are proposed. Micro-movements of a head for representatives of the control group (with a confirmed absence of COVID-19 disease) and a group of patients with a confirmed diagnosis of COVID-19 were studied using vibraimage technology. Parameters and criteria for the diagnosis of COVID-19 for training artificial intelligence (AI) on the control group and the patient group are proposed. 3-layer (one hidden layer) feedforward neural network (40 + 20 + 1 sigmoid neurons) was developed for AI training. AI was firstly trained on the primary sample of patients and a control group. Study of a random sample of people with trained AI was carried out and the possibility of detecting COVID-19 using the proposed method was proved a week before the onset of clinical symptoms of the disease. Number of COVID-19 diagnostic parameters was increased to 26 and AI was trained on a sample of 536 measurements, 268 patient measurement results and 268 measurement results in the control group. The achieved diagnostic accuracy was more than 99%, 4 errors per 536 measurements (2 false positive and 2 false negative), specificity 99.25% and sensitivity 99.25%. The issues of improving the accuracy and reliability of the proposed method for diagnosing COVID-19 are discussed. Further ways to improve the characteristics and applicability of the proposed method of diagnosis and self-diagnosis of COVID-19 are outlined.

Introduction. Multiple sclerosis (MS) is a chronic progressive disease of the central nervous system, which is characterized by demyelination and degeneration of nerve fibers and has a polymorphic clinical picture and a tendency to an unfavourable course [1]. The disease usually affects young and working-age people, leading to early disability and poor quality of life, which makes it a socially significant problem of our time [2]. The main objective was to increase the efficiency of diagnosis and treatment of patients with multiple sclerosis based on a comprehensive analysis of clinical-neurological, psychodiagnostic, and neuroimaging features of the onset and course of the disease. Materials and Methods: Clinical and neurological examination of patients using the Functional System Score (FSS) and Expanded Disability Status Scale (EDSS); cognitive functions examination using the Mini-Mental State Examination (MMSE), the clock-drawing test, the five-word test; brain magnetic resonance imaging; the 36-Item Short Form Health Survey (SF-36). According to statistics, there are about 3 million patients with multiple sclerosis worldwide. In Ukraine, about 20,000 people have multiple sclerosis. Currently, a hypothesis has been made about multiple sclerosis as a multifactorial disease that is, to a great extent, attributable to genetic predisposition (i. e., features of the immune reaction) and the influence of external factors [1]. Multiple sclerosis mainly affects young and mature people – 12 to 55 years old. Although multiple sclerosis can sometimes make its debut in puberty, however, the frequency of the disease gradually increases with age up to the middle of the third decade of life, with a subsequent decrease up to the age of 50–60 [3]. Recently, a trend toward the rejuvenation of multiple sclerosis has been observed. About 3% of all patients with multiple sclerosis are children under 16. Multiple sclerosis debuting at a later age is not sufficiently studied and is rarely diagnosed, although in about 20% of patients, the first signs of this pathology appear after age 40 [4, 11].