Damir Perisa

12 papers receiving 545 citations

Peers

Damir Perisa
Comparison fields: 5 of 82
  • Endocrinology, Diabetes and Metabolism 188
  • Modeling and Simulation 32
  • Clinical Biochemistry 46
  • Cancer Research 91
  • Cardiology and Cardiovascular Medicine 105
Replace Xunliang Tong with:
Xunliang Tong China
Berenice Rivera‐Paredez Mexico
James Shepherd United States
Brian Lam United States
Josep M. Simó Spain
Carole Verhoeven Netherlands
L. A. Ross United States
Mohamed Janabi Tanzania
Rosmawati Mohamed Malaysia
Damir Perisa relative to Xunliang Tong China Xunliang Tong's profile →
Citations per field
00.5×3.4×
Xunliang Tong · 1×
Citations per year

Countries citing papers authored by Damir Perisa

Since Specialization
Citations

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

Fields of papers citing papers by Damir Perisa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Damir Perisa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Damir Perisa Line = papers co-authored together Damir Perisa links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2013277
2 202177
3 200946
4 201735
5 201331
6 201124
7 201520
8 202116
9 202115
10 201910
11
From testing to mortality: COVID-19 and the inverse care law in switzerland
20213
12 20211

About Damir Perisa

Damir Perisa is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism, Molecular Biology, Epidemiology and Health, having authored 12 papers that have together received 555 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), Cholesterol and Lipid Metabolism (3 papers), COVID-19 epidemiological studies (2 papers), Health disparities and outcomes (2 papers), Caveolin-1 and cellular processes (2 papers), Mycobacterium research and diagnosis (2 papers), Lipid metabolism and disorders (2 papers) and Atherosclerosis and Cardiovascular Diseases (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (188 citations), Modeling and Simulation (32 citations), Clinical Biochemistry (46 citations), Cancer Research (91 citations) and Cardiology and Cardiovascular Medicine (105 citations). Damir Perisa has collaborated with scholars based in Switzerland, South Africa and United States. Frequent co-authors include Arnold von Eckardstein, Lucia Rohrer, Meliana Riwanto, Pavani Mocharla, Lukas Altwegg, Kathrin Heinrich, Christian Besler, Thomas F. Lüscher, Bernd Roschitzki and Ulf Landmesser. Their work appears in journals such as Arteriosclerosis Thrombosis and Vascular Biology, Journal of Bacteriology, Vaccine, Journal of Biological Chemistry and Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids.

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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