John B. Colby

1.0k citations
18 papers · 729 · h-index 14

Impact in

Papers in

John B. Colby

18 papers receiving 721 citations

Peers

John B. Colby
Comparison fields: 5 of 81
  • Computational Mathematics 11
  • Radiology, Nuclear Medicine and Imaging 302
  • Cognitive Neuroscience 242
  • Psychiatry and Mental health 142
  • Neurology 56
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Peter Neher Germany
Julio E. Villalón‐Reina United States
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M Symms United Kingdom
Sophia I. Thomopoulos United States
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Yung‐Chin Hsu Taiwan
Kiran Seunarine United Kingdom
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Citations per year

Countries citing papers authored by John B. Colby

Since Specialization
Citations

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

Fields of papers citing papers by John B. Colby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

18 of 18 papers shown
#Work
1 2011181
2 2012105
3 201059
4 201357
5 201447
6 201240
7 202138
8 201537
9 201332
10 201930
11 201326
12 200521
13 202216
14 202116
15 202412
16 201810
17 19721
18
Development of human brain connectivity in health and disease
20121

About John B. Colby

John B. Colby is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Pediatrics, Perinatology and Child Health, Psychiatry and Mental health and Pulmonary and Respiratory Medicine, having authored 18 papers that have together received 729 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (6 papers), Advanced Neuroimaging Techniques and Applications (5 papers), Neonatal and fetal brain pathology (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Alzheimer's disease research and treatments (2 papers), Brain Tumor Detection and Classification (2 papers), Brain Metastases and Treatment (2 papers) and Advanced MRI Techniques and Applications (2 papers). The work is most often cited by research in Computational Mathematics (11 citations), Radiology, Nuclear Medicine and Imaging (302 citations), Cognitive Neuroscience (242 citations), Psychiatry and Mental health (142 citations) and Neurology (56 citations). John B. Colby has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Elizabeth R. Sowell, Jeffrey D. Rudie, Paul M. Thompson, Catherine Lebel, Ivo D. Dinov, John D. Van Horn, Zarrar Shehzad, Jesse A. Brown, Mark S. Cohen and Pamela K. Douglas. Their work appears in journals such as Radiology Artificial Intelligence, Psychiatry Research Neuroimaging, NeuroImage, Frontiers in Systems Neuroscience and Journal of Neuroscience.

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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