Noa Urman

681 citations
37 papers · 551 · h-index 8

Impact in

Papers in

    • Glioma Diagnosis and Treatment 15
    • Wireless Body Area Networks 6
    • 3D Printing in Biomedical Research 5
    • Microfluidic and Bio-sensing Technologies 4

Noa Urman

32 papers receiving 523 citations

Peers

Noa Urman
Comparison fields: 5 of 56
  • Genetics 220
  • Structural Biology 20
  • Biophysics 35
  • Biotechnology 47
  • Cellular and Molecular Neuroscience 83
Replace Shay Cahal with:
Shay Cahal United States
Roni Blat Switzerland
Anders Rosendal Korshoej Denmark
Narasimha Kumar Karanam United States
Einav Zeevi United States
Adrian Kinzel Germany
Aaron Yang United States
Julia Grosch Germany
Ola Rominiyi United Kingdom
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Citations per field
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Shay Cahal · 1×
Citations per year

Countries citing papers authored by Noa Urman

Since Specialization
Citations

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

Fields of papers citing papers by Noa Urman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015250
2 2019103
3 201664
4 202132
5 201925
6 201516
7 201614
8 20197
9 20165
10 20234
11 20154
12 20183
13 20173
14 20152
15 20182
16 20231
17 20231
18 20171
19 20191
20 20231

About Noa Urman

Noa Urman is a scholar working on Genetics, Biomedical Engineering, Radiation, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 37 papers that have together received 551 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (15 papers), Advanced Radiotherapy Techniques (10 papers), Wireless Body Area Networks (6 papers), Cell Image Analysis Techniques (6 papers), Radiation Therapy and Dosimetry (5 papers), 3D Printing in Biomedical Research (5 papers), Microfluidic and Bio-sensing Technologies (4 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). The work is most often cited by research in Genetics (220 citations), Structural Biology (20 citations), Biophysics (35 citations), Biotechnology (47 citations) and Cellular and Molecular Neuroscience (83 citations). Noa Urman has collaborated with scholars based in Switzerland, United States and Portugal. Frequent co-authors include Zéev Bomzon, Eilon D. Kirson, Uri Weinberg, Yoram Palti, Moshe Giladi, Matthew T. Ballo, Gitit Lavy-Shahaf, Shay Cahal, Tali Voloshin and Mijal Munster. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Cancer Research, Neuro-Oncology, Journal of Clinical Oncology and Annals of Oncology.

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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