30 results match your criteria: "National Aerospace University Kharkiv Aviation Institute[Affiliation]"

Objective: To identify the early predictors of a self-reported persistence of long COVID syndrome (LCS) at 12 months after hospitalisation and to propose the prognostic model of its development.

Design: A combined cross-sectional and prospective observational study.

Setting: A tertiary care hospital.

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Article Synopsis
  • Modern AI solutions struggle with the "black box" nature of deep learning models, particularly in critical medical applications where transparency is essential.
  • This study introduces a scalable method using a transition matrix to make deep learning model decisions more interpretable, integrating clinical guidelines and expert rules to ensure alignment with medical standards.
  • Tested on ECG and MRI datasets, the approach showed high agreement with expert annotations (0.89 for ECG and 0.80 for MRI), proving its reliability and potential for broader use in various medical fields.
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Introduction: Recent advancements in generative AI, exemplified by ChatGPT, hold promise for healthcare applications such as decision-making support, education, and patient engagement. However, rigorous evaluation is crucial to ensure reliability and safety in clinical contexts. This scoping review explores ChatGPT's role in clinical inquiry, focusing on its characteristics, applications, challenges, and evaluation.

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Natural Language Processing (NLP) is a subset of artificial intelligence that enables machines to understand and respond to human language through Large Language Models (LLMs)‥ These models have diverse applications in fields such as medical research, scientific writing, and publishing, but concerns such as hallucination, ethical issues, bias, and cybersecurity need to be addressed. To understand the scientific community's understanding and perspective on the role of Artificial Intelligence (AI) in research and authorship, a survey was designed for corresponding authors in top medical journals. An online survey was conducted from July 13th, 2023, to September 1st, 2023, using the SurveyMonkey web instrument, and the population of interest were corresponding authors who published in 2022 in the 15 highest-impact medical journals, as ranked by the Journal Citation Report.

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Generative AI models, such as ChatGPT, have significantly impacted healthcare through the strategic use of prompts to enhance precision, relevance, and ethical standards. This perspective explores the application of prompt engineering to tailor outputs specifically for healthcare stakeholders: patients, providers, policymakers, and researchers. A nine-stage process for prompt engineering in healthcare is proposed, encompassing identifying applications, understanding stakeholder needs, designing tailored prompts, iterative testing and refinement, ethical considerations, collaborative feedback, documentation, training, and continuous updates.

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Application of artificial intelligence in active assisted living for aging population in real-world setting with commercial devices - A scoping review.

Comput Biol Med

May 2024

School of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada; Department of Systems Design Engineering, University of Waterloo, ON, Canada; Centre for Digital Therapeutics, Techna Institute, University Health Network, Toronto, ON, Canada; Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada. Electronic address:

Background: The aging population is steadily increasing, posing new challenges and opportunities for healthcare systems worldwide. Technological advancements, particularly in commercially available Active Assisted Living devices, offer a promising alternative. These readily accessible products, ranging from smartwatches to home automation systems, are often equipped with Artificial Intelligence capabilities that can monitor health metrics, predict adverse events, and facilitate a safer living environment.

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Article Synopsis
  • AI chatbots can change the way people seek health information online by providing personalized and timely responses to health-related questions.
  • They have the ability to counteract the spread of misinformation by analyzing large amounts of data and generating accurate information.
  • However, their effectiveness is limited by challenges such as the need for diverse training data, security issues, and the ongoing requirement for updates to stay current with scientific developments.
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The rapid dissemination of information has been accompanied by the proliferation of fake news, posing significant challenges in discerning authentic news from fabricated narratives. This study addresses the urgent need for effective fake news detection mechanisms. The spread of fake news on digital platforms has necessitated the development of sophisticated tools for accurate detection and classification.

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Background: Post-COVID-19 syndrome (PCS) has been increasingly recognized as an emerging problem: 50% of patients report ongoing symptoms 1 year after acute infection, with most typical manifestations (fatigue, dyspnea, psychiatric and neurological symptoms) having potentially debilitating effect. Early identification of high-risk candidates for PCS development would facilitate the optimal use of resources directed to rehabilitation of COVID-19 convalescents.

Objective: To study the in-hospital clinical characteristics of COVID-19 survivors presenting with self-reported PCS at 3 months and to identify the early predictors of its development.

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Introduction: Non-Fungible Tokens (NFTs) are digital assets that are verified using blockchain technology to ensure authenticity and ownership. NFTs have the potential to revolutionize healthcare by addressing various issues in the industry.

Method: The goal of this study was to identify the applications of NFTs in healthcare.

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Introduction: In the principles of the organization of armed struggle of the defense forces of most developed countries of the world, considerable attention is paid to the evaluation of combat readiness of the military personnel. This procedure is conditioned by such interconnected goals of the armed struggle as the maximum realization of the combat potential and the minimization of personnel losses. The purpose of the work is to determine the physiological cost of the activities of the soldiers of the Defense Forces of Ukraine with the help of miniature electrocardiographic hardware and software complexes.

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Carbon fibres used as a honeycomb core material (subject to a proper in-depth analysis of their reinforcement patterns) allows solving the thermo-dimensional stability problem of the units for space systems. Based on the results of numerical simulations with the support of finite element analysis, the paper provides an evaluation of the accuracy of analytical dependencies for the determination of the moduli of elasticity of a carbon fibre honeycomb core in tension/compression and shear. It is shown that a carbon fibre honeycomb reinforcement pattern has a significant impact on the mechanical performance of the carbon fibre honeycomb core.

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The article projects the components of the intelligent decision support system for epidemiological diagnostics and investigates their interaction with the user. The system includes a bank of models and machine learning methods, a bank of population dynamics models, visualization and reporting tools, and management decision-making unit. The concept of information technology to ensure biosafety of the population is provided.

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Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of death for 32% of the world's population. Particularly relevant are automated diagnostics using machine learning methods in the digitalization of healthcare and introduction of personalized medicine in healthcare institutions, including at the individual level when designing smart houses. Therefore, this study aims to analyze short 10-s electrocardiogram measurements taken from 12 leads.

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The problems of decision support for epidemiological diagnostics are investigated. The basis for supporting decision-making is mathematical tools for analyzing morbidity data, as well as modeling of epidemic processes. The current state of research in this area is analyzed.

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Determination of the Composite Panel Moulding Pressure Value.

Polymers (Basel)

June 2022

Institute of Automotive Engineering, Brno University of Technology, Technická 2896/2, 616 69 Brno, Czech Republic.

Currently, prefabricated panel structures are typical products made of polymeric composite materials. The integrity of the composite panels, their structure and accuracy of making a contour are largely associated with the manifestation of residual technological stresses. The above phenomena and associated stress-strain behaviour inevitably occur in the process of moulding of the composite products.

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Currently, we observe extensive use of products made of polymeric composite materials in various industries. These materials are being increasingly used to manufacture large-sized structural parts that bear significant loads. However, increase in the volume of composites used in critical structures is impeded by the instability of properties of the resulting products.

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COVID-19 has impacted all areas of human activity around the world. Modern society has not faced such a challenge. Affordable travel and flights between continents allowed the virus to rapidly spread to all corners of the world.

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Objective: The aim: The purpose of this article is to analyze the state policy of several states in creating an effective mechanism in which persons entering into marriage will be able to obtain the necessary information about the state of each other's health and thereby make an informed decision about registering a marriage, protecting the health of each other and future offspring.

Patients And Methods: Materials and methods: In the course of the study, a comparative analysis of the legal means used by some states in the field of biological protection of marriage was carried out. First of all, a study was carried out of the family legislation of states with different approaches to the system of premarital medical examination of persons entering into marriage.

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Repair procedures with the use of composite patches are considered to be the most effective among the current technologies of repair of the structures of various applications. In the process of moulding-on of a patch made of polymeric composite material by means of curing, technological stresses arise in the patch. Determination of residual technological stresses is a priority task for the modelling of the repair process.

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Stress-Strain Behaviour of Reparable Composite Panel with Step-Variable Thickness.

Polymers (Basel)

November 2021

Institute of Automotive Engineering, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2896/2, 616 69 Brno, Czech Republic.

There is an urgent problem of finding an economically viable method of maintenance and restoration of the bearing capacity of structures of various applications. Repair of structures with patches made of polymeric composite materials is one of the most promising repair technologies. However, an improper choice of parameters of the composite patch leads to unjustified increase in the structure mass and the cost of its further operation.

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Self-Heating Mould for Composite Manufacturing.

Polymers (Basel)

September 2021

Institute of Automotive Engineering, Brno University of Technology, Technická 2896/2, 616 69 Brno, Czech Republic.

The shipbuilding industry, engine manufacturing, aviation, rocket and space technology are promising fields of application for polymeric composite materials. Shape-generating moulding tools with internal heating are used for the creation of a more economically viable method of moulding of internally heated composite structures. The use of a fine-fibered resistive structure in the heated tools allows implementation of effective heating of the composite and elimination of the need for expensive and energy-intensive heating equipment.

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Objective: The aim: To study the peculiarities of demyelination by detection of changes in the levels of myelin basic protein (MBP) in CSF of patients with acute herpesviral meningitis (M) and meningoencephalitis (ME).

Patients And Methods: Materials and methods: A total of 136 CSF samples from 68 patients with herpesviral M and ME were collected. The control group consisted of patients with acute respiratory infection and meningismus.

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