Martin Možina
- Artificial Intelligence top 5%
- Molecular Biology
- Information Systems top 5%
- Neurology top 10%
- Biomedical Engineering
- Co-authors
- Janez DemšarBlaž ZupanMiran BrvarTomaž CurkMarinka ŽitnikLan UmekMiha ŠtajdoharJure Žbontar
- Topics
- Topic Modeling (8 papers)Natural Language Processing Techniques (5 papers)AI-based Problem Solving and Planning (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaScientific ReportsCritical Care Medicine
- Partner nations
- SloveniaSwedenUnited Kingdom
In The Last Decade
Martin Možina
41 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 205
- Artificial Intelligence 376
- Molecular Biology 328
- Information Systems 120
- Neurology 104
- Biomedical Engineering 103
Countries citing papers authored by Martin Možina
This map shows the geographic impact of Martin Možina'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 Martin Možina with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Možina more than expected).
Fields of papers citing papers by Martin Možina
This network shows the impact of papers produced by Martin Možina. 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 Martin Možina. The network helps show where Martin Možina may publish in the future.
Co-authorship network of co-authors of Martin Možina
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Možina. A scholar is included among the top collaborators of Martin Možina 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 Martin Možina. Martin Možina is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Arguments in Interactive Machine Learning | 2 |
| 3 | 15 | |
| 4 | Orange: data mining toolbox in pythonbreakdown → | 1239 |
| 5 | 13 | |
| 6 | 13 | |
| 7 | Learning to Explain with ABML. | 3 |
| 8 | 86 | |
| 9 | 10 | |
| 10 | DRUG POISONING IN SLOVENIA | 2 |
| 11 | 9 | |
| 12 | Argument Based Rule Learning | 6 |
| 13 | 28 | |
| 14 | 7 | |
| 15 | Calcium channel blocker poisoning | 2 |
| 16 | 3 | |
| 17 | 47 | |
| 18 | 23 | |
| 19 | 13 | |
| 20 | 12 |
About Martin Možina
Martin Možina is a scholar working on Toxicology, Geriatrics and Gerontology and Emergency Medicine, having authored 41 papers that have together received 1.9k indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (5 papers) and AI-based Problem Solving and Planning (4 papers). The work is most often cited by research in Toxicology (100 citations), Geriatrics and Gerontology (96 citations) and Biophysics (72 citations). Martin Možina has collaborated with scholars based in Slovenia, Sweden and United Kingdom. Frequent co-authors include Janez Demšar, Blaž Zupan, Miran Brvar, Tomaž Curk, Marinka Žitnik, Lan Umek, Miha Štajdohar, Jure Žbontar, Marko Toplak and Lan Žagar. Their work appears in journals such as SHILAP Revista de lepidopterología, Scientific Reports and Critical Care Medicine.
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.