Bryan Conroy

1.8k citations
27 papers · 1.3k · h-index 14

Impact in

Papers in

Bryan Conroy

26 papers receiving 1.3k citations

Peers

Bryan Conroy
Comparison fields: 5 of 83
  • Cognitive Neuroscience 672
  • Computational Mathematics 6
  • Health Informatics 22
  • Cardiology and Cardiovascular Medicine 183
  • Pulmonary and Respiratory Medicine 188
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Citations per year

Countries citing papers authored by Bryan Conroy

Since Specialization
Citations

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

Fields of papers citing papers by Bryan Conroy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011453
2 2016239
3 2009137
4 201382
5 201874
6 201849
7 202246
8 201744
9 201539
10
fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity.
200933
11 201626
12 202123
13
Fast, Exact Model Selection and Permutation Testing for ℓ2-Regularized Logistic Regression.
201219
14 201719
15
Fast, Exact Model Selection and Permutation Testing for l2-Regularized Logistic Regression
201213
16 201313
17 202312
18 20102
19 20112
20 20242

About Bryan Conroy

Bryan Conroy is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Health Information Management, Epidemiology and Cardiology and Cardiovascular Medicine, having authored 27 papers that have together received 1.3k indexed citations. Recurring topics across this work include Machine Learning in Healthcare (5 papers), Functional Brain Connectivity Studies (5 papers), Sepsis Diagnosis and Treatment (3 papers), Artificial Intelligence in Healthcare (3 papers), ECG Monitoring and Analysis (3 papers), Neural and Behavioral Psychology Studies (2 papers), Non-Invasive Vital Sign Monitoring (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Cognitive Neuroscience (672 citations), Computational Mathematics (6 citations), Health Informatics (22 citations), Cardiology and Cardiovascular Medicine (183 citations) and Pulmonary and Respiratory Medicine (188 citations). Bryan Conroy has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Peter J. Ramadge, James V. Haxby, Saman Parvaneh, Asif Rahman, Cristhian Potes, J. Swaroop Guntupalli, Yaroslav O. Halchenko, Andrew C. Connolly, Maria Ida Gobbini and Michael Hanke. Their work appears in journals such as Scientific Reports, Critical Care, NeuroImage, Physiological Measurement and Frontiers in Medicine.

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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