
Tijana ŠušteršičUniversity of Kragujevac · Faculty of Engineering
Tijana Šušteršič
About
62
Publications
21,204
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
532
Citations
Introduction
Skills and Expertise
Publications
Publications (62)
Introduction/Objective. The main aim of this study was to assess COVID-19 vaccination effectiveness (VE) of BBIBP-CorV, Gam-COVID-Vac, BNT162b2, and ChAdOx1-nCoV-19 in Serbia during the first three months of rollout. Methods. The data from the Serbian National Immunization Registry, the Primary Health Centre Report and the University Clinical Centr...
Layer-by-layer film (LbL) coatings made of polyelectrolytes are a powerful tool for surface modification, including the applications in the biomedical field, for food packaging, and in many electrochemical systems. However, despite the number of publications related to LbL assembly, predicting LbL coating properties represents quite a challenge, ca...
Introduction/Objective. The duration of vaccine-induced protection against SARS-CoV-2 is shown to be limited. The aim of this study was to assess vaccine effectiveness (VE) of a third dose of four different COVID-19 vaccines during Delta variant predominance in Serbia. Methods. The data for the period from Aug 18th to Oct 1st 2021, were used to est...
Localization of lumbar discs in magnetic resonance imaging (MRI) is a challenging task, due to a vast range of shape, size, number, and appearance of discs and vertebrae. Based on a review of the cutting-edge methods, the majority of applied techniques are either semi-automatic, extremely sensitive to change in parameters, or involve further modifi...
The development of novel dry powders for dry powder inhalers (DPIs) requires the in vitro assessment of DPI aerodynamic performance. As a potential complementary method, in silico numerical simulations can provide additional information about the mechanisms that guide the particles and their behavior inside DPIs. The aim of this study was to apply...
The purpose of the SGABU platform is to include various models and datasets in the area of multiscale modelling. The main aspect of SGABU platform are various datasets and multiscale models related to cancer, cardiovascular, bone and tissue disorders. From the point of view of the dataset integration, a task requires implementation of the user inte...
Background and objective
: In silico clinical trials are the future of medicine and virtual testing and simulation are the future of medical engineering. The use of a computational platform can reduce costs and time required for developing new models of medical devices and drugs. The computational platform, which is one of the main results of the S...
The aim of this research is to create a medical expert system based on Bayes theorem to diagnose level of disc hernia based on real foot force measurement signals obtained using sensors and implement the whole system on field programable gate array (FPGA). We have created a database of attributes based on recorded foot force values of 33 patients p...
The reaction to and the effect severity on the population of COVID-19 varied across different countries. This indicates that there are country-level factors which influenced the severity COVID-19 effect on the populace. The goal of this research is to determine some of these factors using Our World in Data COVID-19 dataset. The performance of the c...
Diagnosing spinal problems is not an easy task. Doctors collect different types of information, including magnetic resonance imaging (MRI), to make a final diagnosis and decision on treatment modality. The localization of lumbar discs on MRI images is a challenging problem due to the wide range of variability in size, shape, number and appearance o...
Coronavirus disease (COVID-19), since its appearance, has put a large burden on the global health system which have strived to mitigate the pandemic, but mortality of COVID-19 continues to increase. Many authors have employed machine learning (ML) algorithms in the investigation of COVID-19 in order to identify infected individuals, predict their c...
The use of artificial intelligence, especially machine learning methods in creating models that will be applied in clinical practice has reached its peak with the appearance of the COVID-19 pandemic. This study aims to determine the severity of the clinical condition of COVID-19 patients based on blood marker analysis. The study used data from 60 C...
Although ML has been examined for a variety of epidemiological and clinical concerns, as well as for COVID-19 survival prediction, there is a notable lack of research dealing with ML utilization in predicting disease severity changes during the course of the disease. This chapter encompasses two approaches in predicting COVID-19 spread—personalized...
Atherosclerotic plaque deposition within the coronary vessel wall leads to arterial stenosis and if not adequately treated, it may potentially have deteriorating consequences, such as a debilitating stroke, thus making early detection of the most importance. The manual plaque components annotation process is both time and resource consuming, theref...
Cardiovascular disease (CVD) is one of the leading causes of death in urban areas. Carotid artery segmentation is the initial step in the automated diagnosis of carotid artery disease. The segmentation of carotid wall and lumen region boundaries are used as an essential part in assessing plaque morphology. In this paper, two types of Convolutional...
SGABU platform was created as a computational platform for multiscale modelling in biomedical engineering. This is one of the few proposed integrated platforms that include different areas of bioengineering. The platform includes already developed solutions, various datasets and models related to cancer, cardiovascular, bone disorders, and tissue e...
While software implementation of various image processing methods is adequate for general application, when it comes to meeting real-time requirements, the implementation has to be performed in hardware. In applications like digital signals and handling massive data in particular in real time, field programmable gate arrays (FPGAs) have many advant...
In vitro assessment of dry powders for inhalation (DPIs) aerodynamic performance is an inevitable test in DPI development. However, contemporary trends in drug development also implicate the use of in silico methods, e.g., computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM). The aim of this study was to compare the designe...
Computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM) appeared as an alternative approach to the commonly used in vitro methods for the assessment of dry powders for inhalation (DPI) aerodynamic properties. The aim of this study was to compare the parameters that describe DPI aerodynamic performance, obtained computationally...
Since the outbreak of coronavirus disease-2019 (COVID-19), the whole world has taken interest in the mechanisms of its spread and development. Mathematical models have been valuable instruments for the study of the spread and control of infectious diseases. For that purpose, we propose a two-way approach in modeling COVID-19 spread: a susceptible,...
The release of metal particles and ions due to wear and corrosion is one of the main underlying reasons for the long-term complications of implantable metallic implants. The rather short-term focus of the established in-vitro biocompatibility tests cannot take into account such effects. Corrosion behavior of metallic implants mostly investigated in...
Background and objectives:
Although ML has been studied for different epidemiological and clinical issues as well as for survival prediction of COVID-19, there is a noticeable shortage of literature dealing with ML usage in prediction of disease severity changes through the course of the disease. In that way, predicting disease progression from mi...
INTRODUCTION: As a result of this global health crisis caused by the COVID-19 pandemic, the medical industry is searching for innovations that have the potential to automate the diagnostic process of COVID-19 and serve as an assistive tool for clinicians.
OBJECTIVES: X-ray images have shown to be useful in the diagnosis of COVID-19. The goal of th...
Since the outbreak of new coronavirus COVID-19, measures for ending the global pandemic such as social distancing and contact tracing have been proposed worldwide. We propose a SEIRD model to predict the development of epidemic, which can contribute to effective planning to control it. Based on official statistical data for Belgium, we calculated t...
Monitoring the fetus during pregnancy and childbirth is a great challenge for the obstetric team. Proper monitoring of the fetus during pregnancy and childbirth is very important in order to detect deviations and complications in a timely manner and thus for a better perinatal outcome for the newborn and the mother. In this paper, a brief descripti...
In this paper, a review of the project Use of Regressive Artificial Intelligence and Machine Learning Methods in Modelling of COVID-19 Spread (COVIDAi) is presented. The main goal of the project is to design two main AI-based models: epidemiological and personalized. After the introduction, a brief description of project partners and activities is...
COVID-19 is one of the greatest challenges humanity has faced recently, forcing a change in the daily lives of billions of people worldwide. Therefore, many efforts have been madebyresearchers across the globe in the attempt of determining the models of COVID-19 spread. The objectives of this review are to analyze some of the open-access datasets m...
Estimation of the epidemiology curve for the COVID-19 pandemic can be a very computationally challenging task. Thus far, there have been some implementations of artificial intelligence (AI) methods applied to develop epidemiology curve for a specific country. However, most applied AI methods generated models that are almost impossible to translate...
COVID-19 represents one of the greatest challenges in modern history. Its impact is most noticeable in the health care system, mostly due to the accelerated and increased influx of patients with a more severe clinical picture. These facts are increasing the pressure on health systems. For this reason, the aim is to automate the process of diagnosis...
The aim of this study was to create a decision support system for disc hernia diagnostics based on real measurements of foot force values from sensors and fuzzy logic, as well as to implement the system on Field Programmable Gate Array (FPGA). The results show that the created fuzzy logic system had the 92.8% accuracy for pre-operational diagnosis...
Background: Systems Medicine is a novel approach to medicine, i.e. an
interdisciplinary field that considers the human body as a system, composed of
multiple parts and of complex relationships at multiple levels, and further
integrated into an environment. Exploring Systems Medicine implies
understanding and combining concepts coming from diametral...
The aim of this research was to investigate the best methodology for disc hernia diagnosis using foot force measurements from the designed platform. Based on the subjective neurological examination that examines muscle weakness on the nerve endings of the skin area on feet and concludes about origins of nerve roots between spine discs, a platform f...
Although software implementations of different image processing techniques are suitable for general-purpose use, in order to meet the real time requirements, an image processing technique needs to be realized in hardware. Field Programmable Gate Arrays (FPGAs) have many benefits in applications that include digital signal acquisition, but also proc...
The aim of this research was to analyze objectively the process of disc herniation identification using Bayes Theorem. One of the symptoms of discus hernia is muscle weakness on the foot that is caused by displaced discs in the space of two vertebrae. This fact is used by experts in initial diagnosis of herniated discs and we used it to create non-...
Since the main purpose of generation of organ-on-chips is to reduce and, at some point, replace experiments on the animals, several different organs were point of interest in developing on-chip technology. The paper will therefore focus on creating mathematical model of liver cell aggregation, generating a basis for creation of artificial organs in...
This chapter will present the use of biomaterials in applications related to tissue engineering and artificial organs and examine how emerging and enabling technologies are being developed and applied, with a strong focus on fundamental and traditional tissue engineering strategies. The primary goal is to provide a systematic overview of the field...
Background: Systems Medicine is a novel approach to medicine, i.e. an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring Systems Medicine implies understanding and combining concepts coming from diametral...
The aim of this work was to investigate effects of the formulation factors on tablet printability as well as to optimize and predict extended drug release from cross-linked polymeric ibuprofen printlets using an artificial neural network (ANN). Printlets were printed using digital light processing (DLP) technology from formulations containing polye...
The overall aim of organ-on-a-chip monitoring model tissues is providing self-reporting tissue models that can either individually or as an integrated platform be used to test the biocompatibility of materials with some emphasis on materials immune compatibility/immune-toxicity. We will focus in this abstract on coupling the experimental data with...
Face recognition has its theoretical and practical value in daily life. In this chapter, we will present face recognition application and discuss its implementation using the Maxeler DataFlow paradigm. We first give theoretical background and overview of the existing solutions in the area of algorithms for face recognition. Maxeler card is based on...
Multiscale modelling has gained importance in simulating different levels of organs [1]. Defining influence of biomaterial presence to cell growth and cell proliferation is a topic of wide research, as well as immune response to biomaterials [2], in order to define level of biomaterial compatibility with innate immune cells and to see if the biomat...
The most important characteristics of the electrospun fibers are their internal morphology and their diameter. They both depend on polymer's parameters, but also on the process parameters. The motivation for this research is therefore to simulate the jet during electrospinning and analyze the effects of some of the parameters on the jet (and implic...
The aim of this research was to investigate if it is possible to implicitly determine the homogeneity of the obtained electrospun fibers based on jet shape during electrospinning. Experiments were performed with 10 wt% PVA solution, and four variations in process parameters were investigated in order to examine their effect on fiber structure. Data...
This paper presents the improved technique for classification of the type of lumbar discus hernia based on fuzzy logic. The reduced mobility of the foot is one of the symptoms of the disease that occurs because of the displaced discs in the space of two vertebrae. This fact was used for non-invasive discus hernia diagnosis by measuring force values...
In vitro models are very important in medicine and biology, because they provide an insight into cells' and microorganisms' behavior. Since these cells and microorganisms are isolated from their natural environment, these models may not completely or precisely predict the effects on the entire organism. Improvement in this area is secured by organ-...
The aim of this study is to implement an algorithm for face recognition, based on fast fourier transform (FFT), on the field programmable gate array (FPGA) chip. Implemented program included the initialization process of two single-IP-core ROM blocks, each with an image of a human face, which are sent to the real components of two-channel IP CoreFF...
Geometry of the bioreactor was created on the basis of the existing literature. Flow of the fluid, containing the monocyte cells, through the bioreactor was analysed. The model was created with open solver PAK and solved with the finite element method, as well as with commercial software ANSYS. The obtained results were compared between the solvers...
Field of face recognition has been developing in the past several decades. Although percentage of successful recognition algorithms is constantly getting higher, there is room for improvement. Field Programmable Gate Array (FPGA) is technology that can be used for speed and accuracy improvement. The main goal of this paper was to load photos from f...
One of the critical components of the respiratory drug delivery is the manner in which the inhaled aerosol is deposited in respiratory tract compartments. Depending on formulation properties, device characteristics and breathing pattern, only a certain fraction of the dose will reach the target site in the lungs, while the rest of the drug will dep...
This paper presents calculation of the pressure gradient at the point of aortic stenosis in patients with valvular aortic stenosis. The pressure gradients obtained by calculation were compared with the pressure gradients measured using catheterization in 12 patients with valvular aortic stenosis. It has been found that the maximum separation factor...