Publications by authors named "M 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.
Aim: To define the role of clinical, endoscopic, laboratory and immunomorphological parameters in predicting the occurrence and course of colorectal cancer (CRC) in patients with diverticular disease of the colon (DDC).
Materials And Methods: One hundred and seventy five people with DDC were examined, divided into 3 groups: group 1 - 85 patients with DDC; group 2 - 45 with DDC in combination with adenomatous polyps (AP); 3rd group - 45 with DDC with established CRC (I or II stage). The control group consisted of 30 practically healthy people.
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.
Background: Rising global concerns about COVID-19 recently gained more research attention due to the ease of person-to-person transmission, various symptoms after healing, and the shortage of effective antiviral therapy. The study aims to analyze post-COVID conditions and clinical manifestations of cardiovascular lesions in patients recovering from COVID-19 infection.
Methods: A practical examination of post-COVID conditions manifestation was conducted in a prospective cohort study, involving 250 patients diagnosed with COVID-19 between June 1, 2021, and August 31, 2021.
A significant prevalence of gastrointestinal symptoms in SARS-CoV-2 infection is also associated with its fecal-oral transmission, which leads to a progressive increase in the number of patients with diseases of the esophagus, stomach and intestines. In addition, intestinal infections caused by SARS-CoV-2 may be one of the main causes of functional long-term stress-related gastrointestinal disorders, united in the concept of post-COVID syndrome.
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