Tijana Šušteršič

570 total citations
35 papers, 324 citations indexed

About

Tijana Šušteršič is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Infectious Diseases. According to data from OpenAlex, Tijana Šušteršič has authored 35 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Biomedical Engineering, 11 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Infectious Diseases. Recurrent topics in Tijana Šušteršič's work include COVID-19 diagnosis using AI (9 papers), Spine and Intervertebral Disc Pathology (5 papers) and COVID-19 epidemiological studies (4 papers). Tijana Šušteršič is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), Spine and Intervertebral Disc Pathology (5 papers) and COVID-19 epidemiological studies (4 papers). Tijana Šušteršič collaborates with scholars based in Serbia, Croatia and Russia. Tijana Šušteršič's co-authors include Nenad Filipović, Svetlana Ibrić, Ivan Lorencin, Sandi Baressi Šegota, Djordje Medarević, Jelena Djuriš, Nikola Anđelić, Tomislav Ćabov, Zlatan Car and Sandra Cvijić and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Environmental Research and Public Health and European Journal of Pharmaceutical Sciences.

In The Last Decade

Tijana Šušteršič

34 papers receiving 321 citations

Peers

Tijana Šušteršič
Lei Song China
Yichuan Ma China
Manman Cui China
Jingjing Chen China
Jagdeep T. Podichetty United States
Maciej Koźlik Poland
Maciej Cebula Poland
David Martínez-Enguita Sweden
Jakub Kufel Poland
Jaesik Kim South Korea
Lei Song China
Tijana Šušteršič
Citations per year, relative to Tijana Šušteršič Tijana Šušteršič (= 1×) peers Lei Song

Countries citing papers authored by Tijana Šušteršič

Since Specialization
Citations

This map shows the geographic impact of Tijana Šušteršič's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tijana Šušteršič with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tijana Šušteršič more than expected).

Fields of papers citing papers by Tijana Šušteršič

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tijana Šušteršič. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tijana Šušteršič. The network helps show where Tijana Šušteršič may publish in the future.

Co-authorship network of co-authors of Tijana Šušteršič

This figure shows the co-authorship network connecting the top 25 collaborators of Tijana Šušteršič. A scholar is included among the top collaborators of Tijana Šušteršič based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tijana Šušteršič. Tijana Šušteršič is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Djordjević, Nataša, Sanja Matić, Dragan Milovanović, et al.. (2023). Effectiveness of a third dose of COVID-19 vaccines against delta variant of SARS-COV-2: A Serbian cohort study. SHILAP Revista de lepidopterología. 151(9-10). 518–524.
2.
Šušteršič, Tijana, et al.. (2023). The Effect of Machine Learning Algorithms on the Prediction of Layer-by-Layer Coating Properties. ACS Omega. 8(5). 4677–4686. 20 indexed citations
3.
Šušteršič, Tijana, et al.. (2022). Numerical Modeling of Particle Dynamics Inside a Dry Powder Inhaler. Pharmaceutics. 14(12). 2591–2591. 1 indexed citations
4.
Filipović, Nenad, et al.. (2022). SILICOFCM platform, multiscale modeling of left ventricle from echocardiographic images and drug influence for cardiomyopathy disease. Computer Methods and Programs in Biomedicine. 227. 107194–107194. 6 indexed citations
5.
Šušteršič, Tijana, et al.. (2022). Development of SGABU Platform for Multiscale Modeling. 18(1). 50–55. 1 indexed citations
6.
Filipović, Nenad, Igor Šaveljić, Tijana Šušteršič, et al.. (2022). <em>In Silico</em> Clinical Trials for Cardiovascular Disease. Journal of Visualized Experiments. 1 indexed citations
7.
Radovanović, N., et al.. (2022). Patch-based Convolutional Neural Network for Atherosclerotic Carotid Plaque Semantic Segmentation. 18(1). 56–61. 2 indexed citations
8.
Radovanović, N., et al.. (2022). Carotid Artery Segmentation Using Convolutional Neural Network in Ultrasound Images. 18(1). 44–49. 2 indexed citations
9.
Anđelić, Nikola, Sandi Baressi Šegota, Ivan Lorencin, et al.. (2021). Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm. International Journal of Environmental Research and Public Health. 18(3). 959–959. 12 indexed citations
10.
Šušteršič, Tijana, Ivan Lorencin, Sandi Baressi Šegota, et al.. (2021). Artificial intelligence approach towards assessment of condition of COVID-19 patients - Identification of predictive biomarkers associated with severity of clinical condition and disease progression. Computers in Biology and Medicine. 138. 104869–104869. 5 indexed citations
11.
Šegota, Sandi Baressi, Ivan Lorencin, Nikola Anđelić, et al.. (2021). Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review. International Journal of Environmental Research and Public Health. 18(8). 4287–4287. 34 indexed citations
12.
Šušteršič, Tijana, Sandra Cvijić, Jelena Đuriš, et al.. (2021). Comparative Assessment of In Vitro and In Silico Methods for Aerodynamic Characterization of Powders for Inhalation. Pharmaceutics. 13(11). 1831–1831. 6 indexed citations
13.
Lorencin, Ivan, Sandi Baressi Šegota, Nikola Anđelić, et al.. (2021). Automatic Evaluation of the Lung Condition of COVID-19 Patients Using X-ray Images and Convolutional Neural Networks. Journal of Personalized Medicine. 11(1). 28–28. 22 indexed citations
14.
Šušteršič, Tijana, et al.. (2021). An In-Silico Corrosion Model for Biomedical Applications for Coupling With In-Vitro Biocompatibility Tests for Estimation of Long-Term Effects. Frontiers in Bioengineering and Biotechnology. 9. 718026–718026. 10 indexed citations
15.
Šušteršič, Tijana, Danijela Cvetković, Ivan Lorencin, et al.. (2021). Epidemiological Predictive Modeling of COVID-19 Infection: Development, Testing, and Implementation on the Population of the Benelux Union. Frontiers in Public Health. 9. 727274–727274. 10 indexed citations
16.
Šegota, Suzana, et al.. (2021). Automated Pipeline for Continual Data Gathering and Retraining of the Machine Learning-Based COVID-19 Spread Models. 1(3). 169582–169582. 1 indexed citations
17.
Šušteršič, Tijana, Vladimir Milovanović, Vesna Ranković, & Nenad Filipović. (2020). A comparison of classifiers in biomedical signal processing as a decision support system in disc hernia diagnosis. Computers in Biology and Medicine. 125. 103978–103978. 4 indexed citations
18.
Peulić, Aleksandar, et al.. (2018). Non-invasive improved technique for lumbar discus hernia classification based on fuzzy logic. Biomedizinische Technik/Biomedical Engineering. 64(4). 421–428. 5 indexed citations
19.
Šušteršič, Tijana, et al.. (2018). In vitro Models and On-Chip Systems: Biomaterial Interaction Studies With Tissues Generated Using Lung Epithelial and Liver Metabolic Cell Lines. Frontiers in Bioengineering and Biotechnology. 6. 120–120. 44 indexed citations
20.
Šušteršič, Tijana, et al.. (2017). Coupled in silico platform: Computational fluid dynamics (CFD) and physiologically-based pharmacokinetic (PBPK) modelling. European Journal of Pharmaceutical Sciences. 113. 171–184. 25 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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