Marcell Nagy

13 papers receiving 202 citations

Peers

Marcell Nagy
Comparison fields: 5 of 56
  • Computer Science Applications 140
  • Health Informatics 16
  • Health Information Management 27
  • Artificial Intelligence 73
  • Statistical and Nonlinear Physics 16
Replace Gomathy Ramaswami with:
Gomathy Ramaswami New Zealand
Therese Kanai United States
Joshua D. Baron United States
Nisha S. Raj India
Everaldo Aguiar United States
Samira ElAtia Canada
Alfred Essa United States
M. Anbarasan India
Weijie Jiang China
Masaki Uto Japan
Marcell Nagy relative to Gomathy Ramaswami New Zealand Gomathy Ramaswami's profile →
Citations per field
00.5×10×16×
Gomathy Ramaswami · 1×
Citations per year

Countries citing papers authored by Marcell Nagy

Since Specialization
Citations

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

Fields of papers citing papers by Marcell Nagy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 10 scholars most cited alongside Marcell Nagy, 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 Marcell Nagy Line = papers co-authored together Marcell Nagy links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201857
2 202047
3 202338
4 201919
5 202114
6 202113
7 20227
8 20224
9 20233
10 20243
11 20253
12 20241
13 20251
14 20230
15 20240

About Marcell Nagy

Marcell Nagy is a scholar working on Artificial Intelligence, Computer Science Applications, Statistical and Nonlinear Physics, Health Informatics and Education, having authored 15 papers that have together received 210 indexed citations. Recurring topics across this work include Online Learning and Analytics (5 papers), Complex Network Analysis Techniques (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Higher Education Learning Practices (3 papers), Mental Health Research Topics (2 papers), Bioinformatics and Genomic Networks (2 papers), Medical Education and Admissions (2 papers) and Explainable Artificial Intelligence (XAI) (2 papers). The work is most often cited by research in Computer Science Applications (140 citations), Health Informatics (16 citations), Health Information Management (27 citations), Artificial Intelligence (73 citations) and Statistical and Nonlinear Physics (16 citations). Marcell Nagy has collaborated with scholars based in Hungary, Italy and Mexico. Frequent co-authors include Roland Molontay, Péter Tamás Kovács, Béla Barabás, Griffin M. Weber, Aldo Ramírez-Arellano, Gyula Pályi, Bruce W. Herr, Ellen M. Quardokus, Katy Börner and Csaba Kiss. Their work appears in journals such as Assessment & Evaluation in Higher Education, Applied Network Science, International Journal of Artificial Intelligence in Education, Fractals and Nature Communications.

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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