Péter Bayer

56 papers receiving 1.1k citations

Péter Bayer's Hit Papers

The Shapley Value in Machine Learning 2022 · 145 citations
1450+1+2Years since publication4080120

Peers

Péter Bayer
Comparison fields: 5 of 145
  • Transplantation 71
  • Rheumatology 189
  • Hematology 128
  • Nephrology 68
  • Pathology and Forensic Medicine 129
Replace Mei‐Chin Wen with:
Mei‐Chin Wen Taiwan
Alessandro Volpe Italy
Shintaro Narita Japan
Jian-Hua Qiao United States
Vipul C. Chitalia United States
Jean Francis United States
Michele Rossini Italy
Michael J. Becich United States
Kazuhiro Nishikawa Japan
LJ Lesko United States
Péter Bayer relative to Mei‐Chin Wen Taiwan Mei‐Chin Wen's profile →
Citations per field
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Mei‐Chin Wen · 1×
Citations per year

Countries citing papers authored by Péter Bayer

Since Specialization
Citations

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

Fields of papers citing papers by Péter Bayer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Péter Bayer, 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 Péter Bayer Line = papers co-authored together Péter Bayer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The Shapley Value in Machine Learning
Hit paper breakdown →
2022145
2 2008124
3 199771
4 200863
5 200362
6 200951
7 199937
8 199234
9 199334
10 198033
11 198127
12
Vascular endothelial growth factor in patients with psoriatic arthritis.
200727
13 199726
14 198025
15 199625
16 199522
17
Whole-blood immunoassay (SimpliRED) versus plasma immunoassay (NycoCard) for the diagnosis of clinically suspected deep vein thrombosis.
199722
18 197621
19 199721
20 200720

About Péter Bayer

Péter Bayer is a scholar working on Hematology, Molecular Biology, Physiology, Immunology and Radiology, Nuclear Medicine and Imaging, having authored 59 papers that have together received 1.1k indexed citations. Recurring topics across this work include Experimental Behavioral Economics Studies (4 papers), Game Theory and Applications (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Pancreatitis Pathology and Treatment (4 papers), Clinical Laboratory Practices and Quality Control (4 papers), Renal Transplantation Outcomes and Treatments (3 papers), Single-cell and spatial transcriptomics (3 papers) and Mast cells and histamine (3 papers). The work is most often cited by research in Transplantation (71 citations), Rheumatology (189 citations), Hematology (128 citations), Nephrology (68 citations) and Pathology and Forensic Medicine (129 citations). Péter Bayer has collaborated with scholars based in Austria, France and United States. Frequent co-authors include Wolfgang Hübl, Stefan Presslauer, Dejan Milosavljevic, Thomas Brücke, Rik Sarkar, Olivér Kiss, Hao-Tsung Yang, Benedek Rózemberczki, Irmgard Neumann and Christian Koeberl. Their work appears in journals such as Clinical Chemistry, Clinical Chemistry and Laboratory Medicine (CCLM), Journal of Clinical Laboratory Analysis, Clinica Chimica Acta and American Journal of Clinical Pathology.

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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