Csaba Huszka

448 citations
9 papers · 349 · h-index 7

Impact in

Papers in

    • Cognitive Science and Mapping 3
    • Cognitive Computing and Networks 2
    • Bayesian Modeling and Causal Inference 2
    • Semantic Web and Ontologies 2
    • AI-based Problem Solving and Planning 1
    • Biomedical Text Mining and Ontologies 2

Csaba Huszka

9 papers receiving 338 citations

Peers

Csaba Huszka
Comparison fields: 5 of 79
  • Developmental Neuroscience 109
  • Cellular and Molecular Neuroscience 134
  • Health Information Management 22
  • Artificial Intelligence 103
  • Health Informatics 4
Replace Andrée Delahaye‐Duriez with:
Andrée Delahaye‐Duriez France
Xulong Wang China
Yao Yan United States
Grace Chung United States
Huy Tien Nguyen Vietnam
Collin J. Engstrom United States
Mathew Abrams Sweden
Pakanat Decharatanachart Thailand
Weichen Song China
Roxana Merino-Martinez Sweden
Csaba Huszka relative to Andrée Delahaye‐Duriez France Andrée Delahaye‐Duriez's profile →
Citations per field
00.5×4.5×
Andrée Delahaye‐Duriez · 1×
Citations per year

Countries citing papers authored by Csaba Huszka

Since Specialization
Citations

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

Fields of papers citing papers by Csaba Huszka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2002190
2 201142
3 201332
4 201325
5 201023
6 201222
7 20207
8 20194
9 20124

About Csaba Huszka

Csaba Huszka is a scholar working on Artificial Intelligence, Molecular Biology, Cellular and Molecular Neuroscience, Cognitive Neuroscience and Computer Networks and Communications, having authored 9 papers that have together received 349 indexed citations. Recurring topics across this work include Cognitive Science and Mapping (3 papers), Cognitive Computing and Networks (2 papers), Bayesian Modeling and Causal Inference (2 papers), Semantic Web and Ontologies (2 papers), Biomedical Text Mining and Ontologies (2 papers), Neurogenesis and neuroplasticity mechanisms (1 paper), AI-based Problem Solving and Planning (1 paper) and Advanced Database Systems and Queries (1 paper). The work is most often cited by research in Developmental Neuroscience (109 citations), Cellular and Molecular Neuroscience (134 citations), Health Information Management (22 citations), Artificial Intelligence (103 citations) and Health Informatics (4 citations). Csaba Huszka has collaborated with scholars based in Belgium, Greece and Germany. Frequent co-authors include Stefan Pollak, Michael Frotscher, M. Kirsch, Josef Zentner, Carola A. Haas, Oliver Dudeck, Jos De Roo, Elpiniki I. Papageorgiou, Marie‐Christine Jaulent and Stefan Schulz. Their work appears in journals such as Computer Methods and Programs in Biomedicine, Epilepsy & Behavior, Language Resources and Evaluation, Journal of Biomedical Informatics and Journal of Neuroscience.

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.

Explore authors with similar magnitude of impact