Aleksander Øhrn

864 total citations
11 papers, 342 citations indexed

About

Aleksander Øhrn is a scholar working on Information Systems, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Aleksander Øhrn has authored 11 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 7 papers in Computational Theory and Mathematics and 6 papers in Artificial Intelligence. Recurrent topics in Aleksander Øhrn's work include Rough Sets and Fuzzy Logic (7 papers), Data Mining Algorithms and Applications (7 papers) and Artificial Intelligence in Healthcare (1 paper). Aleksander Øhrn is often cited by papers focused on Rough Sets and Fuzzy Logic (7 papers), Data Mining Algorithms and Applications (7 papers) and Artificial Intelligence in Healthcare (1 paper). Aleksander Øhrn collaborates with scholars based in Norway, United States and Poland. Aleksander Øhrn's co-authors include Staal A. Vinterbo, Lucila Ohno‐Machado, Jan Komorowski, Hamish Fraser, Andrzej Skowron, Klev Diamanti, Lars Feuk, Susanne Bornelöv and Piotr Szymański and has published in prestigious journals such as BMC Bioinformatics, American Journal of Physical Medicine & Rehabilitation and Artificial Intelligence in Medicine.

In The Last Decade

Aleksander Øhrn

11 papers receiving 301 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Aleksander Øhrn Norway	9	181	180	139	29	23	11	342
Chien-I Lee Taiwan	7	177 1.0×	63 0.3×	114 0.8×	21 0.7×	15 0.7×	23	295
Bhabesh Nath India	8	225 1.2×	154 0.9×	244 1.8×	37 1.3×	8 0.3×	22	358
Hanna Wasyluk Poland	7	168 0.9×	46 0.3×	79 0.6×	22 0.8×	17 0.7×	11	355
Sam Yuan Sung Singapore	10	158 0.9×	52 0.3×	97 0.7×	65 2.2×	11 0.5×	36	287
Duy-Tai Dinh Japan	10	181 1.0×	70 0.4×	155 1.1×	60 2.1×	9 0.4×	18	288
Raj Bhatnagar United States	11	166 0.9×	62 0.3×	72 0.5×	49 1.7×	79 3.4×	55	377
R. Alhajj Canada	8	220 1.2×	99 0.6×	166 1.2×	47 1.6×	5 0.2×	16	330
Jianchao Han United States	8	98 0.5×	41 0.2×	123 0.9×	35 1.2×	16 0.7×	47	281
Zongtian Liu China	11	195 1.1×	114 0.6×	112 0.8×	43 1.5×	13 0.6×	77	325
Andrés R. Masegosa Spain	12	272 1.5×	69 0.4×	71 0.5×	18 0.6×	14 0.6×	24	383

Countries citing papers authored by Aleksander Øhrn

Since Specialization

Citations

This map shows the geographic impact of Aleksander Øhrn'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 Aleksander Øhrn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aleksander Øhrn more than expected).

Fields of papers citing papers by Aleksander Øhrn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aleksander Øhrn. 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 Aleksander Øhrn. The network helps show where Aleksander Øhrn may publish in the future.

Co-authorship network of co-authors of Aleksander Øhrn

This figure shows the co-authorship network connecting the top 25 collaborators of Aleksander Øhrn. A scholar is included among the top collaborators of Aleksander Øhrn 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 Aleksander Øhrn. Aleksander Øhrn is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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11 of 11 papers shown

1.

Diamanti, Klev, et al.. (2021). R.ROSETTA: an interpretable machine learning framework. BMC Bioinformatics. 22(1). 110–110. 15 indexed citations

2.

Komorowski, Jan, Aleksander Øhrn, & Andrzej Skowron. (2002). Case studies: Public domain, multiple mining tasks systems: ROSETTA rough sets. Oxford University Press eBooks. 554–559. 5 indexed citations

3.

Øhrn, Aleksander. (2001). ROSETTA Technical Reference Manual. 28(5). 247–52. 64 indexed citations

4.

Vinterbo, Staal A. & Aleksander Øhrn. (2000). Minimal approximate hitting sets and rule templates. International Journal of Approximate Reasoning. 25(2). 123–143. 95 indexed citations

5.

Øhrn, Aleksander, et al.. (2000). Rough Sets: A Knowledge Discovery Technique for Multifactorial Medical Outcomes. American Journal of Physical Medicine & Rehabilitation. 79(1). 100–108. 24 indexed citations

6.

Komorowski, Jan & Aleksander Øhrn. (1999). Modelling prognostic power of cardiac tests using rough sets. Artificial Intelligence in Medicine. 15(2). 167–191. 52 indexed citations

7.

Øhrn, Aleksander & Lucila Ohno‐Machado. (1999). Using Boolean reasoning to anonymize databases. Artificial Intelligence in Medicine. 15(3). 235–254. 45 indexed citations

8.

Ohno‐Machado, Lucila, Hamish Fraser, & Aleksander Øhrn. (1998). Improving machine learning performance by removing redundant cases in medical data sets.. PubMed. 523–7. 14 indexed citations

9.

Ohno‐Machado, Lucila, et al.. (1998). Comparison of multiple prediction models for ambulation following spinal cord injury.. PubMed. 528–32. 18 indexed citations

10.

Øhrn, Aleksander, et al.. (1998). Building manageable rough set classifiers.. PubMed. 543–7. 8 indexed citations

11.

Øhrn, Aleksander, Staal A. Vinterbo, Piotr Szymański, & Jan Komorowski. (1997). Modelling cardiac patient set residuals using rough sets.. PubMed. 203–7. 2 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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