Arman Rahman

1.4k citations
35 papers · 678 · h-index 15

Impact in

    • Aquaculture disease management and microbiota
    • Immune Cell Function and Interaction
    • T-cell and B-cell Immunology
    • Immune Response and Inflammation

Papers in

    • Immune Response and Inflammation 3
    • T-cell and B-cell Immunology 3
    • Biochemical and Structural Characterization 2

Arman Rahman

32 papers receiving 663 citations

Peers

Arman Rahman
Comparison fields: 5 of 109
  • Health Informatics 20
  • Immunology 194
  • Microbiology 49
  • Aquatic Science 42
  • Cancer Research 56
Replace Xiaoling Liu with:
Xiaoling Liu China
Sherry Bhalla India
Kensuke Tomio Japan
Sunil K. Malonia United States
Justin Bo‐Kai Hsu Taiwan
Keith M. Callenberg United States
Yun Tan China
Arjen Companjen Netherlands
Haihe Wang China
Puthen V. Jithesh Qatar
Arman Rahman relative to Xiaoling Liu China Xiaoling Liu's profile →
Citations per field
00.5×10×
Xiaoling Liu · 1×
Citations per year

Countries citing papers authored by Arman Rahman

Since Specialization
Citations

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

Fields of papers citing papers by Arman Rahman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014114
2 1998104
3 200150
4 201034
5 200932
6 202229
7 202128
8 201728
9 202027
10 200727
11 202026
12 202026
13 202425
14 201123
15 202220
16 200514
17 202011
18 201710
19 20139
20 20209

About Arman Rahman

Arman Rahman is a scholar working on Immunology, Molecular Biology, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Cancer Research, having authored 35 papers that have together received 678 indexed citations. Recurring topics across this work include AI in cancer detection (6 papers), Antimicrobial Peptides and Activities (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Immune Response and Inflammation (3 papers), Cancer Genomics and Diagnostics (3 papers), T-cell and B-cell Immunology (3 papers), Cancer Immunotherapy and Biomarkers (3 papers) and Biochemical and Structural Characterization (2 papers). The work is most often cited by research in Health Informatics (20 citations), Immunology (194 citations), Microbiology (49 citations), Aquatic Science (42 citations) and Cancer Research (56 citations). Arman Rahman has collaborated with scholars based in Ireland, Sweden and United Kingdom. Frequent co-authors include Takeshi Matsunaga, William M. Gallagher, Gillian O’Hurley, Cecilia Lindskog, Bo Li, Fredrik Pontén, Evelina Sjöstedt, Caroline Kampf, Marie‐Louise Hammarström and Sten Hammarström. Their work appears in journals such as Expert Review of Molecular Diagnostics, Journal of Clinical Oncology, Cancer Research, Cancers and Journal of Personalized Medicine.

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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