Ivan Lorencin
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Health Informatics top 10%
Papers in
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- AI in cancer detection 10
- Evolutionary Algorithms and Applications 7
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- COVID-19 epidemiological studies 7
- Co-authors
- Nikola Anđelić (49 shared papers)Zlatan Car (47 shared papers)Vedran Mrzljak (26 shared papers)Sandi Baressi Šegota (42 shared papers)Josip Španjol (6 shared papers)Milan Sága (1 shared paper)Tomislav Ćabov (4 shared papers)Nenad Filipović (7 shared papers)
In The Last Decade
Ivan Lorencin
75 papers receiving 1k citations
Peers
Comparison fields: 5 of 104
- Modeling and Simulation 94
- Health Informatics 37
- Artificial Intelligence 244
- Health Information Management 48
- Control and Systems Engineering 134
Countries citing papers authored by Ivan Lorencin
This map shows the geographic impact of Ivan Lorencin'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 Ivan Lorencin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ivan Lorencin more than expected).
Fields of papers citing papers by Ivan Lorencin
This network shows the impact of papers produced by Ivan Lorencin. 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 Ivan Lorencin. The network helps show where Ivan Lorencin may publish in the future.
Co-authors
The 23 scholars most cited alongside Ivan Lorencin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 155 | |
| 2 | 2019 | 122 | |
| 3 | 2019 | 79 | |
| 4 | 2020 | 58 | |
| 5 | 2021 | 42 | |
| 6 | 2021 | 36 | |
| 7 | 2019 | 34 | |
| 8 | 2023 | 34 | |
| 9 | 2019 | 29 | |
| 10 | 2023 | 29 | |
| 11 | 2019 | 28 | |
| 12 | 2019 | 26 | |
| 13 | 2020 | 24 | |
| 14 | 2021 | 24 | |
| 15 | 2022 | 24 | |
| 16 | 2021 | 23 | |
| 17 | 2021 | 20 | |
| 18 | 2020 | 15 | |
| 19 | 2024 | 14 | |
| 20 | 2021 | 13 |
About Ivan Lorencin
Ivan Lorencin is a scholar working on Artificial Intelligence, Modeling and Simulation, Computer Vision and Pattern Recognition, Control and Systems Engineering and Health Information Management, having authored 81 papers that have together received 1.1k indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Thermodynamic and Exergetic Analyses of Power and Cooling Systems (9 papers), Advanced Neural Network Applications (8 papers), Evolutionary Algorithms and Applications (7 papers), COVID-19 epidemiological studies (7 papers), Advanced Power Generation Technologies (5 papers), Artificial Intelligence in Healthcare (5 papers) and Robotic Mechanisms and Dynamics (5 papers). The work is most often cited by research in Modeling and Simulation (94 citations), Health Informatics (37 citations), Artificial Intelligence (244 citations), Health Information Management (48 citations) and Control and Systems Engineering (134 citations). Ivan Lorencin has collaborated with scholars based in Croatia, Serbia and Slovakia. Frequent co-authors include Nikola Anđelić, Zlatan Car, Vedran Mrzljak, Sandi Baressi Šegota, Josip Španjol, Milan Sága, Tomislav Ćabov, Nenad Filipović, Tijana Geroski and Ivan Kuric. Their work appears in journals such as Electronics, Applied Sciences, Big Data and Cognitive Computing, International Journal of Environmental Research and Public Health and Biology.
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.