Daniel D. Callow

1.0k citations
34 papers · 666 · h-index 14

Impact in

Papers in

Daniel D. Callow

30 papers receiving 654 citations

Peers

Daniel D. Callow
Comparison fields: 5 of 92
  • Health 119
  • Cognitive Neuroscience 199
  • Neuropsychology and Physiological Psychology 14
  • Clinical Psychology 176
  • Physiology 160
Replace Junyeon Won with:
Junyeon Won United States
Gabriel S. Pena United States
Hayley Guiney New Zealand
Leslie Jordan United States
Ellen W. Yeung United States
Katja Waller Finland
Belén Frades‐Payo Spain
Teresa Bobes-Bascarán Spain
Anna MacKay‐Brandt United States
Natan Feter Brazil
Daniel D. Callow relative to Junyeon Won United States Junyeon Won's profile →
Citations per field
00.5×1.5×2.3×
Junyeon Won · 1×
Citations per year

Countries citing papers authored by Daniel D. Callow

Since Specialization
Citations

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

Fields of papers citing papers by Daniel D. Callow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel D. Callow. 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 Daniel D. Callow. The network helps show where Daniel D. Callow may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020227
2 202162
3 202039
4 201938
5
Multifaceted effects of astragaloside IV on promotion of random pattern skin flap survival in rats.
201732
6 202129
7 201926
8 201723
9 202123
10 201921
11 202116
12 202114
13 202213
14 202113
15 202012
16 202111
17 202310
18 202210
19 20238
20 20227

About Daniel D. Callow

Daniel D. Callow is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Physiology, Cardiology and Cardiovascular Medicine and Neurology, having authored 34 papers that have together received 666 indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (14 papers), Advanced Neuroimaging Techniques and Applications (7 papers), Dementia and Cognitive Impairment Research (6 papers), Heart Rate Variability and Autonomic Control (6 papers), Sleep and related disorders (4 papers), COVID-19 and Mental Health (4 papers), Advanced MRI Techniques and Applications (3 papers) and Vestibular and auditory disorders (3 papers). The work is most often cited by research in Health (119 citations), Cognitive Neuroscience (199 citations), Neuropsychology and Physiological Psychology (14 citations), Clinical Psychology (176 citations) and Physiology (160 citations). Daniel D. Callow has collaborated with scholars based in United States and China. Frequent co-authors include Junyeon Won, Gabriel S. Pena, J. Carson Smith, Leslie Jordan, Naomi A. Arnold-Nedimala, John L. Woodard, J. Carson Smith, Michael Callow, Lauren R. Weiss and Alfonso J. Alfini. Their work appears in journals such as Journal of the International Neuropsychological Society, Neuropsychologia, Journal of Applied Gerontology, Neurobiology of Aging and Hippocampus.

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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