Michael Kellen

2.2k citations
11 papers · 986 · 1 hit paper · h-index 8

Impact in

Papers in

Michael Kellen

11 papers receiving 964 citations

Michael Kellen's Hit Papers

The mPower study, Parkinson disease mobile data collected using ResearchKit 2016 · 451 citations
4510+3+6Years since publication100200300400

Peers

Michael Kellen
Comparison fields: 5 of 130
  • Health Informatics 18
  • Applied Psychology 58
  • Cancer Research 145
  • Neurology 138
  • Human-Computer Interaction 50
Replace Brian M. Bot with:
Brian M. Bot United States
Christine Suver United States
J Christopher Bare United States
Megan Doerr United States
Catherine A. Brownstein United States
Ralf Schmidmaier Germany
Minyoung Lee South Korea
Heidi Howard Belgium
Amos Folarin United Kingdom
James Heywood United States
Michael Kellen relative to Brian M. Bot United States Brian M. Bot's profile →
Citations per field
00.5×1.5×2.3×
Brian M. Bot · 1×
Citations per year

Countries citing papers authored by Michael Kellen

Since Specialization
Citations

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

Fields of papers citing papers by Michael Kellen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1
The mPower study, Parkinson disease mobile data collected using ResearchKit
Hit paper breakdown →
2016451
2 2015190
3 201697
4 201377
5 201957
6 201239
7 200338
8 200326
9 20217
10 20243
11 20221

About Michael Kellen

Michael Kellen is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Genetics, Cancer Research and Communication, having authored 11 papers that have together received 986 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (2 papers), Bioinformatics and Genomic Networks (2 papers), Cardiovascular Function and Risk Factors (2 papers), Genomics and Rare Diseases (1 paper), Cardiac electrophysiology and arrhythmias (1 paper), Cardiovascular Health and Disease Prevention (1 paper), Gene expression and cancer classification (1 paper) and Wikis in Education and Collaboration (1 paper). The work is most often cited by research in Health Informatics (18 citations), Applied Psychology (58 citations), Cancer Research (145 citations), Neurology (138 citations) and Human-Computer Interaction (50 citations). Michael Kellen has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Stephen Friend, J Christopher Bare, Brian M. Bot, Christine Suver, Elias Chaibub Neto, Abhishek Pratap, Andrew D. Trister, Arno Klein, E. Ray Dorsey and John Wilbanks. Their work appears in journals such as American Journal of Physiology-Heart and Circulatory Physiology, Nature Genetics, JMIR mhealth and uhealth, Neurology and Scientific Data.

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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