John M. Aronis

917 citations
29 papers · 568 · h-index 13

Impact in

Papers in

    • Machine Learning in Healthcare 3
    • Anomaly Detection Techniques and Applications 3
    • Data Mining Algorithms and Applications 7
    • Information Systems Education and Curriculum Development 3

John M. Aronis

29 papers receiving 511 citations

Peers

John M. Aronis
Comparison fields: 5 of 120
  • Computer Science Applications 99
  • Health Informatics 12
  • Health Information Management 38
  • Gender Studies 64
  • Artificial Intelligence 218
Replace Brendan Flanagan with:
Brendan Flanagan Japan
Ralph Morelli United States
Matthew D. Pistilli United States
Martin Hlosta United Kingdom
David Eichmann United States
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Vinícius R. P. Borges Brazil
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Citations per field
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Citations per year

Countries citing papers authored by John M. Aronis

Since Specialization
Citations

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

Fields of papers citing papers by John M. Aronis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Aronis. 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 John M. Aronis. The network helps show where John M. Aronis may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997140
2 2006100
3 200543
4 200334
5 199628
6 199827
7 199826
8
Increasing the efficiency of data mining algorithms with Breadth-first marker propagation
199717
9
Exploiting background knowledge in automated discovery
199615
10 199715
11 200315
12 199814
13 199613
14 201712
15
Efficiently constructing relational features from background knowledge for inductive machine learning
199411
16
Plant exposures: a state profile of the most common species.
199611
17 200010
18
The WoRLD: Knowledge Discovery from Multiple Distributed Databases
19977
19 19967
20
Identifying patient subgroups with simple Bayes'.
19996

About John M. Aronis

John M. Aronis is a scholar working on Artificial Intelligence, Information Systems, Epidemiology, Computer Science Applications and Molecular Biology, having authored 29 papers that have together received 568 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (7 papers), Data-Driven Disease Surveillance (6 papers), Gender and Technology in Education (4 papers), Teaching and Learning Programming (4 papers), Machine Learning in Healthcare (3 papers), Anomaly Detection Techniques and Applications (3 papers), Influenza Virus Research Studies (3 papers) and Information Systems Education and Curriculum Development (3 papers). The work is most often cited by research in Computer Science Applications (99 citations), Health Informatics (12 citations), Health Information Management (38 citations), Gender Studies (64 citations) and Artificial Intelligence (218 citations). John M. Aronis has collaborated with scholars based in United States. Frequent co-authors include Mary Lou Soffa, David Allbritton, Foster Provost, Bruce G. Buchanan, Sandra Katz, Edward P. Krenzelok, Christine Brown Wilson, Teresa Jacobsen, Tom M. Mitchell and Constantin Aliferis. Their work appears in journals such as Machine Learning, Journal of Biomedical Informatics, PLoS ONE, The American Journal of Emergency Medicine and First Monday.

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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