Amin Naemi

18 papers receiving 211 citations

Peers

Amin Naemi
Comparison fields: 5 of 67
  • Health Informatics 16
  • Virology 37
  • Health Information Management 10
  • Radiology, Nuclear Medicine and Imaging 36
  • Reproductive Medicine 13
Replace Tetsuo Ishikawa with:
Tetsuo Ishikawa Japan
Hoon Dong Kim South Korea
Thomas J. Fuchs United States
Marko Notar Slovenia
Ramsey M. Wehbe United States
Grace Choi United States
Reina Komatsu Japan
Adi Szeskin Israel
Sreekar Mantena United States
Krishna Nand Keshava Murthy United States
Amin Naemi relative to Tetsuo Ishikawa Japan Tetsuo Ishikawa's profile →
Citations per field
00.5×10×15×18.5×
Tetsuo Ishikawa · 1×
Citations per year

Countries citing papers authored by Amin Naemi

Since Specialization
Citations

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

Fields of papers citing papers by Amin Naemi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 19 scholars most cited alongside Amin Naemi, 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 Amin Naemi Line = papers co-authored together Amin Naemi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202255
2 202345
3 202135
4 202425
5 202116
6 202115
7 20254
8 20203
9 20223
10 20253
11 20243
12 20203
13 20241
14 20211
15 20251
16 20251
17 20191
18 20211
19 20250
20 20260

About Amin Naemi

Amin Naemi is a scholar working on Artificial Intelligence, Epidemiology, Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging and Emergency Medicine, having authored 22 papers that have together received 216 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (3 papers), Substance Abuse Treatment and Outcomes (2 papers), Emergency and Acute Care Studies (2 papers), Topic Modeling (2 papers), Alcohol Consumption and Health Effects (2 papers), Retinal Imaging and Analysis (1 paper), Brain Tumor Detection and Classification (1 paper) and Telemedicine and Telehealth Implementation (1 paper). The work is most often cited by research in Health Informatics (16 citations), Virology (37 citations), Health Information Management (10 citations), Radiology, Nuclear Medicine and Imaging (36 citations) and Reproductive Medicine (13 citations). Amin Naemi has collaborated with scholars based in Denmark, Iran and Netherlands. Frequent co-authors include Uffe Kock Wiil, Habibollah Pirnejad, Jamshid Bagherzadeh, Marjan Mansourvar, Thomas Schmidt, Ali Ebrahimi, Mohammad Naghavi‐Behzad, Anette Søgaard Nielsen, Donald E. Canfield and Ghulam Mujtaba. Their work appears in journals such as BMC Medical Informatics and Decision Making, Scientific Reports, BMJ Open, Proceedings of the National Academy of Sciences and BMC Infectious Diseases.

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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