Janos Hajagos

87 total papers · 2.0k total citations
25 papers, 543 citations indexed

About

Janos Hajagos is a scholar working on Artificial Intelligence, Molecular Biology and Statistics, Probability and Uncertainty. According to data from OpenAlex, Janos Hajagos has authored 25 papers receiving a total of 543 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 7 papers in Molecular Biology and 5 papers in Statistics, Probability and Uncertainty. Recurrent topics in Janos Hajagos's work include Biomedical Text Mining and Ontologies (7 papers), Machine Learning in Healthcare (5 papers) and Probabilistic and Robust Engineering Design (5 papers). Janos Hajagos is often cited by papers focused on Biomedical Text Mining and Ontologies (7 papers), Machine Learning in Healthcare (5 papers) and Probabilistic and Robust Engineering Design (5 papers). Janos Hajagos collaborates with scholars based in United States, Ireland and Netherlands. Janos Hajagos's co-authors include Scott Ferson, Elgar Pichler, Michael S. Marshall, Susie Stephens, Eric Prud’hommeaux, Egon Willighagen, Matthias Samwald, Joel Saltz, Mary Saltz and Anja Jentzsch and has published in prestigious journals such as Journal of the American Medical Informatics Association, Reliability Engineering & System Safety and Surgical Endoscopy.

In The Last Decade

Janos Hajagos

24 papers receiving 512 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Janos Hajagos	181	132	130	99	73	25	543
Gailing Li	107 0.6×	134 1.0×	76 0.6×	51 0.5×	73 1.0×	24	497
Sallie Keller‐McNulty	129 0.7×	18 0.1×	98 0.8×	36 0.4×	93 1.3×	49	491
Elias Zafiropoulos	191 1.1×	57 0.4×	63 0.5×	22 0.2×	53 0.7×	15	604
Hojin Moon	193 1.1×	156 1.2×	17 0.1×	29 0.3×	36 0.5×	34	601
Kandethody M. Ramachandran	56 0.3×	27 0.2×	27 0.2×	46 0.5×	50 0.7×	27	557
William R. Myers	36 0.2×	46 0.3×	96 0.7×	121 1.2×	147 2.0×	33	576
Alexis Boukouvalas	94 0.5×	160 1.2×	23 0.2×	43 0.4×	37 0.5×	23	591
Madeleine Udell	186 1.0×	49 0.4×	12 0.1×	73 0.7×	37 0.5×	41	617
Hyoung‐Moon Kim	145 0.8×	59 0.4×	74 0.6×	35 0.4×	32 0.4×	47	543
Megan Kaiser	235 1.3×	196 1.5×	20 0.2×	15 0.2×	35 0.5×	14	481

Countries citing papers authored by Janos Hajagos

Since Specialization

Citations

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

Fields of papers citing papers by Janos Hajagos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Janos Hajagos

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

All Works

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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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