Rok Blagus
Impact in
-
- Artificial Intelligence in Healthcare
- Parasitology top 5%
- Vector-borne infectious diseases
Papers in
-
- Imbalanced Data Classification Techniques 9
- Parasitology 10
- Vector-borne infectious diseases 8
- Co-authors
- Lara Lusa (9 shared papers)Rok Orel (5 shared papers)Modest Vengušt (8 shared papers)Daša Stupica (9 shared papers)Tjaša Cerar (8 shared papers)Bojan Leskošek (8 shared papers)Gregor Starc (6 shared papers)M. Ocepek (4 shared papers)
- Journals
- BMC Bioinformatics (5 papers)Muscle & Nerve (3 papers)PLoS ONE (3 papers)Journal of Forensic Sciences (2 papers)BioMed Research International (2 papers)
- Partner nations
- SloveniaSwitzerlandUnited States
In The Last Decade
Rok Blagus
86 papers receiving 2.3k citations
Rok Blagus's Hit Papers
Peers
Comparison fields: 5 of 181
- Health Information Management 110
- Parasitology 112
- Artificial Intelligence 582
- Infectious Diseases 169
- Gastroenterology 48
Countries citing papers authored by Rok Blagus
This map shows the geographic impact of Rok Blagus'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 Rok Blagus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rok Blagus more than expected).
Fields of papers citing papers by Rok Blagus
This network shows the impact of papers produced by Rok Blagus. 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 Rok Blagus. The network helps show where Rok Blagus may publish in the future.
Co-authors
The 25 scholars most cited alongside Rok Blagus, 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 92 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | SMOTE for high-dimensional class-imbalanced data Hit paper breakdown → | 2013 | 784 |
| 2 | 2010 | 200 | |
| 3 | 2021 | 120 | |
| 4 | 2015 | 95 | |
| 5 | 2012 | 77 | |
| 6 | 2016 | 68 | |
| 7 | 2014 | 58 | |
| 8 | 2010 | 55 | |
| 9 | 2013 | 44 | |
| 10 | 2012 | 38 | |
| 11 | 2016 | 36 | |
| 12 | 2013 | 33 | |
| 13 | 2011 | 33 | |
| 14 | 2015 | 30 | |
| 15 | 2019 | 30 | |
| 16 | 2012 | 27 | |
| 17 | 2014 | 24 | |
| 18 | 2018 | 24 | |
| 19 | 2018 | 23 | |
| 20 | 2018 | 23 |
About Rok Blagus
Rok Blagus is a scholar working on Artificial Intelligence, Parasitology, Infectious Diseases, Surgery and Public Health, Environmental and Occupational Health, having authored 92 papers that have together received 2.4k indexed citations. Recurring topics across this work include Imbalanced Data Classification Techniques (9 papers), Vector-borne infectious diseases (8 papers), Obesity, Physical Activity, Diet (5 papers), COVID-19 epidemiological studies (4 papers), Statistical Methods and Inference (4 papers), Statistical Methods and Bayesian Inference (4 papers), Clostridium difficile and Clostridium perfringens research (3 papers) and Physical Activity and Health (3 papers). The work is most often cited by research in Health Information Management (110 citations), Parasitology (112 citations), Artificial Intelligence (582 citations), Infectious Diseases (169 citations) and Gastroenterology (48 citations). Rok Blagus has collaborated with scholars based in Slovenia, Switzerland and United States. Frequent co-authors include Lara Lusa, Rok Orel, Modest Vengušt, Daša Stupica, Tjaša Cerar, Bojan Leskošek, Gregor Starc, M. Ocepek, Gaj Vidmar and Blaž Krhin. Their work appears in journals such as BMC Bioinformatics, Muscle & Nerve, PLoS ONE, Journal of Forensic Sciences and BioMed Research International.
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.