Balázs Bánfai

4.6k citations
11 papers · 997 indexed · 1 hit paper · h-index 7
Topics
Pesticide Residue Analysis and Safety (4 papers)Statistical Methods in Clinical Trials (4 papers)Advanced Statistical Process Monitoring (3 papers)

In The Last Decade

Balázs Bánfai

11 papers receiving 977 citations

Hit Papers

An Introduction to Machine Learning20202026202220242020100200300400500

Peers

Balázs Bánfai
Comparison fields: 5 of 171
  • Molecular Biology 441
  • Cancer Research 266
  • Artificial Intelligence 110
  • Biomedical Engineering 63
  • Spectroscopy 57
Replace Carlos Fernández-Lozano with:
Carlos Fernández-Lozano Spain
Chunyu Wang China
Gaurav Pandey United States
Mohamed Ghalwash United States
Hyoeun Kim South Korea
Rizwan Qureshi Pakistan
Yu Tian China
Saurav Mallik India
Hak‐Soo Kim South Korea
Juliane Siebourg‐Polster Switzerland
Balázs Bánfai relative to Carlos Fernández-Lozano Spain Carlos Fernández-Lozano's profile →
Citations per field
00.5×6.0×
Carlos Fernández-Lozano · 1×
Citations per year

Countries citing papers authored by Balázs Bánfai

Since Specialization
Citations

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

Fields of papers citing papers by Balázs Bánfai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Balázs Bánfai

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1
An Introduction to Machine Learningbreakdown →
503
2 21
3 92
4 20
5 7
6 319
7 1
8 3
9 5
10 2
11 24

About Balázs Bánfai

Balázs Bánfai is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Software, having authored 11 papers that have together received 997 indexed citations. Recurring topics across this work include Pesticide Residue Analysis and Safety (4 papers), Statistical Methods in Clinical Trials (4 papers) and Advanced Statistical Process Monitoring (3 papers). The work is most often cited by research in Cancer Research (266 citations), Health Informatics (21 citations) and Molecular Biology (441 citations). Balázs Bánfai has collaborated with scholars based in Switzerland, Hungary and United States. Frequent co-authors include Jitao David Zhang, Iakov I. Davydov, Solveig Badillo, Lucy Hutchinson, Tony Kam‐Thong, Fabian Birzele, Bernhard Steiert, Juliane Siebourg‐Polster, Peter J. Bickel and Ling Xie. Their work appears in journals such as Scientific Reports, Genome Research and Journal of Chromatography A.

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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