Behdad Behnam

27 papers receiving 541 citations

Peers

Behdad Behnam
Comparison fields: 5 of 97
  • Biological Psychiatry 179
  • Behavioral Neuroscience 70
  • Health Informatics 25
  • Neurology 78
  • Psychiatry and Mental health 125
Replace Lalit Gupta with:
Lalit Gupta India
Sanskriti Varma United States
Thiago Macedo e Cordeiro Brazil
Vishwadeep Ahluwalia United States
Xiaoqian Luan China
Ai Kimura Japan
Anna Giulia Bottaccioli Italy
Lana Fani Netherlands
Chryssa Pourzitaki Greece
Liying Miao China
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Citations per field
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Citations per year

Countries citing papers authored by Behdad Behnam

Since Specialization
Citations

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

Fields of papers citing papers by Behdad Behnam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007229
2 202074
3 202050
4 202031
5 201728
6 202327
7 201620
8 201511
9 202110
10
Warfarin-induced Eosinophilia in a Child with urkitt Lymphoma: A Case Report.
20159
11 20169
12
Correlation of MRI findings and cognitive function in multiple sclerosis patients using montreal cognitive assessment test.
20168
13 20157
14 20177
15 20177
16
Successful Nonsurgical Treatment of a Radial Artery Pseudoaneurysm Following Transradial Coronary Angiography.
20174
17 20194
18 20163
19 20203
20 20203

About Behdad Behnam

Behdad Behnam is a scholar working on Neurology, Pathology and Forensic Medicine, Cardiology and Cardiovascular Medicine, Psychiatry and Mental health and Infectious Diseases, having authored 29 papers that have together received 554 indexed citations. Recurring topics across this work include Long-Term Effects of COVID-19 (4 papers), COVID-19 Clinical Research Studies (4 papers), Multiple Sclerosis Research Studies (4 papers), Dementia and Cognitive Impairment Research (2 papers), Erythrocyte Function and Pathophysiology (2 papers), Venous Thromboembolism Diagnosis and Management (2 papers), Neurological Disorders and Treatments (2 papers) and COVID-19 diagnosis using AI (1 paper). The work is most often cited by research in Biological Psychiatry (179 citations), Behavioral Neuroscience (70 citations), Health Informatics (25 citations), Neurology (78 citations) and Psychiatry and Mental health (125 citations). Behdad Behnam has collaborated with scholars based in Iran and United Kingdom. Frequent co-authors include Mehran Arab Ahmadi, S. A. Abbasi, Shahin Akhondzadeh, Heresh Amini, Maryam Tabatabaee, Alireza Abrishami, Peyman Mohammadi Torbati, Farzad Ashrafi, Nooshin Dalili and Morteza Sanei Taheri. Their work appears in journals such as Neurological Sciences, Schizophrenia Research, Journal of Forensic and Legal Medicine, European Journal of Nutrition and European Urology.

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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