Arash Mohtashamian

1.2k citations
11 papers · 567 indexed · 1 hit paper · h-index 4

Arash Mohtashamian

9 papers receiving 551 citations

Hit Papers

Development and validation of a deep learning algorithm f...3022019202620212023100200300

Peers

Arash Mohtashamian
Comparison fields: 5 of 85
  • Health Informatics 118
  • Radiology, Nuclear Medicine and Imaging 312
  • Artificial Intelligence 386
  • Biophysics 50
  • Health Information Management 20
Replace Lily H. Peng with:
Lily H. Peng United States
Kunal Nagpal United States
Andrew Zhang United States
Norman Zerbe Germany
Sharifa Sahai United States
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Arash Mohtashamian relative to Lily H. Peng United States Lily H. Peng's profile →
Citations per field
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Citations per year

Countries citing papers authored by Arash Mohtashamian

Since Specialization
Citations

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

Fields of papers citing papers by Arash Mohtashamian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

11 of 11 papers shown
#Work
1 20241
2 20243
3 20241
4 20231
5 20230
6 20222
7
Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancerbreakdown →
2019302
8 2018246
9 20160
10 20146
11 20105

About Arash Mohtashamian

Arash Mohtashamian is a scholar working on Hematology, Genetics and Cancer Research, having authored 11 papers that have together received 567 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (3 papers), Lymphoma Diagnosis and Treatment (2 papers), Sarcoma Diagnosis and Treatment (1 paper), Extracellular vesicles in disease (1 paper), Digital Imaging in Medicine (1 paper) and Prostate Cancer Diagnosis and Treatment (1 paper). The work is most often cited by research in Health Informatics (118 citations), Radiology, Nuclear Medicine and Imaging (312 citations) and Artificial Intelligence (386 citations). Arash Mohtashamian has collaborated with scholars based in United States, Italy and Canada. Frequent co-authors include Niels Olson, Lily H. Peng, Martin C. Stumpe, Jenny L. Smith, Jason Hipp, Yun Liu, George E. Dahl, Mohammad Norouzi, Timo Kohlberger and Andrew Evans. Their work appears in journals such as Journal of Clinical Oncology, Archives of Pathology & Laboratory Medicine, npj Digital Medicine, Head and Neck Pathology and Journal of Pathology Informatics.

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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