Mat Soukup

1.3k citations
9 papers · 235 · h-index 6

Impact in

Papers in

    • Statistical Methods in Clinical Trials 4
    • Statistical Methods and Inference 1
    • Advanced Causal Inference Techniques 1
    • Gene expression and cancer classification 2
    • Biomedical Text Mining and Ontologies 1

Mat Soukup

9 papers receiving 231 citations

Peers

Mat Soukup
Comparison fields: 5 of 57
  • Emergency Medicine 94
  • Virology 35
  • Statistics and Probability 36
  • Infectious Diseases 64
  • Statistics, Probability and Uncertainty 11
Replace Casimir Ledoux Sofeu with:
Casimir Ledoux Sofeu France
Cynthia H. Brothers United States
Thomas Kelleher United States
Ricky Hsu United States
Gill Pearce United States
Cassidy Henegar United States
Rachel Ceccarelli United States
Marit G. A. van Vonderen Netherlands
Sumanth Karamchand South Africa
Larry Peiperl United States
Mat Soukup relative to Casimir Ledoux Sofeu France Casimir Ledoux Sofeu's profile →
Citations per field
00.5×8.7×
Casimir Ledoux Sofeu · 1×
Citations per year

Countries citing papers authored by Mat Soukup

Since Specialization
Citations

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

Fields of papers citing papers by Mat Soukup

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2012132
2 201532
3 201824
4 200520
5 200411
6 20096
7 20155
8 20203
9 20222

About Mat Soukup

Mat Soukup is a scholar working on Statistics and Probability, Molecular Biology, Economics and Econometrics, Computer Vision and Pattern Recognition and Toxicology, having authored 9 papers that have together received 235 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (4 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), Gene expression and cancer classification (2 papers), Statistical Methods and Inference (1 paper), Biomedical Text Mining and Ontologies (1 paper), Advanced Causal Inference Techniques (1 paper), HIV-related health complications and treatments (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Emergency Medicine (94 citations), Virology (35 citations), Statistics and Probability (36 citations), Infectious Diseases (64 citations) and Statistics, Probability and Uncertainty (11 citations). Mat Soukup has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Cynthia Kornegay, Kendall A. Marcus, Xiao Ding, Charles K. Cooper, Peter Miele, Matthew A. Psioda, Joseph G. Ibrahim, HyungJun Cho, Jae K. Lee and Brenda Crowe. Their work appears in journals such as Statistics in Medicine, Journal of Biopharmaceutical Statistics, Dermatologic Therapy, Journal of Bioinformatics and Computational Biology and JAIDS Journal of Acquired Immune Deficiency Syndromes.

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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