Bryan Conroy

1.9k citations
26 papers · 1.2k · h-index 14

Impact in

Papers in

    • Neural dynamics and brain function 5
    • Functional Brain Connectivity Studies 4
    • Visual perception and processing mechanisms 3
    • EEG and Brain-Computer Interfaces 3
    • Machine Learning in Healthcare 4

Bryan Conroy

23 papers receiving 1.2k citations

Peers

Bryan Conroy
Comparison fields: 5 of 106
  • Cognitive Neuroscience 763
  • Cardiology and Cardiovascular Medicine 263
  • Radiology, Nuclear Medicine and Imaging 221
  • Signal Processing 93
  • Health Informatics 9
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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 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011420
2 2016216
3 2009121
4 201874
5 201374
6 201850
7 201743
8 201534
9 202233
10
fMRI-Based Inter-Subject Cortical Alignment Using Functional Connectivity.
200931
11 201721
12
Fast, Exact Model Selection and Permutation Testing for ℓ2-Regularized Logistic Regression.
201219
13 202117
14 201715
15
Fast, Exact Model Selection and Permutation Testing for l2-Regularized Logistic Regression
201213
16 20138
17
Function-based Intersubject Alignment of Human Cortical Anatomy
20097
18 20234
19 20102
20
Phenotyping with Prior Knowledge using Patient Similarity
20201

About Bryan Conroy

Bryan Conroy is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Epidemiology, Cardiology and Cardiovascular Medicine and Radiology, Nuclear Medicine and Imaging, having authored 26 papers that have together received 1.2k indexed citations. Recurring topics across this work include Sepsis Diagnosis and Treatment (5 papers), Neural dynamics and brain function (5 papers), Functional Brain Connectivity Studies (4 papers), Machine Learning in Healthcare (4 papers), Hemodynamic Monitoring and Therapy (3 papers), Visual perception and processing mechanisms (3 papers), EEG and Brain-Computer Interfaces (3 papers) and ECG Monitoring and Analysis (3 papers). The work is most often cited by research in Cognitive Neuroscience (763 citations), Cardiology and Cardiovascular Medicine (263 citations), Radiology, Nuclear Medicine and Imaging (221 citations), Signal Processing (93 citations) and Health Informatics (9 citations). Bryan Conroy has collaborated with scholars based in United States, Italy and Finland. Frequent co-authors include Peter J. Ramadge, James V. Haxby, Saman Parvaneh, Asif Rahman, J. Swaroop Guntupalli, Cristhian Potes, M. Ida Gobbini, Yaroslav O. Halchenko, Michael Hanke and Andrew C. Connolly. Their work appears in journals such as Scientific Reports, NeuroImage, Critical Care, Vaccine and Machine Learning.

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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