Publications by authors named "Mikhail Osadchuk"

Article Synopsis
  • The research focuses on creating a machine learning algorithm to diagnose COVID-19 from chest X-rays using transfer learning and support vector machines, utilizing data from 10 clinics and a total of 10,000 X-ray images.
  • Results indicated high accuracy rates for the proposed model with 95% for COVID-19, 89% for pneumonia, and 92% for normal cases, outperforming several other advanced models in terms of sensitivity and overall performance.
  • The study highlights the potential of machine learning in medical diagnostics, showcasing the model's effectiveness across various clinical settings and its ability to maintain consistency between predicted and actual results.
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Background: In recent years, researchers have focused on developing precise models for the progression of Alzheimer's disease (AD) using deep neural networks. Forecasting the progression of AD through the analysis of time series data represents a promising approach.

Objective: The primary objective of this research is to formulate an effective methodology for forecasting the progression of AD through the integration of multi-task learning techniques and the analysis of pertinent medical data.

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Background: The aim of this study is to identify the influence of factors that determine the refusal of influenza vaccine among three subjects groups.

Methods: A survey was conducted amongst three high‑risk groups in years 2018-2019 (Moscow, Russia). The survey involved 1,620 parents and pregnant women (group 1), 324 doctors (group 2) and 433 students (group 3).

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Purpose: Influenza is the most common seasonal infectious disease that causes permanent social, economic, and medical problems worldwide. Therefore, the most effective way to prevent influenza is through vaccines. The aim of this study is to identify the influence of factors that determine the refusal of influenza vaccine among three subjects groups.

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The goal was to determine ways to optimize diagnostic and therapeutic measures for various types of melasma in the outpatient setting of the dermatovenerological ambulatory clinic. The study involved 112 women with a confirmed diagnosis of facial melasma whose disease lasted for at least 2 years. The severity of patient pigmentation was evaluated using the Melasma Area Severity Index and the Melasma Severity Scale.

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Article Synopsis
  • - The study focuses on the prevalence and characteristics of tick-borne borreliosis in the Moscow region, highlighting it as the most common tick-transmitted disease in parts of Europe, Asia, and North America.
  • - Researchers collected and analyzed 2,537 ticks over several months, observing that one tick species significantly outnumbered the other during various periods, particularly in late spring and early autumn.
  • - Findings revealed that 30% of ticks were infected with borreliosis, with higher infestation rates near populated areas; tick populations were influenced by temperature (optimal between 20°C-25°C) and humidity (above 50%).
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