Guy Nir

1.4k citations
27 papers · 1.1k · h-index 14

Impact in

Papers in

Guy Nir

27 papers receiving 1.1k citations

Peers

Guy Nir
Comparison fields: 5 of 112
  • Health Informatics 97
  • Radiology, Nuclear Medicine and Imaging 467
  • Artificial Intelligence 456
  • Pulmonary and Respiratory Medicine 285
  • Computer Vision and Pattern Recognition 197
Replace Jihye Yun with:
Jihye Yun South Korea
Oliver Diaz Montesdeoca Spain
Niels H. Olson United States
Avishek Chatterjee Netherlands
Pingjun Chen United States
Mark J. Gooding United Kingdom
Satish E. Viswanath United States
Arash Mohtashamian United States
Kunal Nagpal United States
Theresa Thai United States
Guy Nir relative to Jihye Yun South Korea Jihye Yun's profile →
Citations per field
00.5×2×4×6×8.4×
Jihye Yun · 1×
Citations per year

Countries citing papers authored by Guy Nir

Since Specialization
Citations

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

Fields of papers citing papers by Guy Nir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019393
2 2018140
3 2019115
4 201981
5 201875
6 201444
7 201742
8 201323
9 201721
10 201419
11 201718
12 201417
13 201817
14 201414
15 201414
16 201313
17 201212
18 201412
19 201311
20 201510

About Guy Nir

Guy Nir is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Artificial Intelligence and Mechanics of Materials, having authored 27 papers that have together received 1.1k indexed citations. Recurring topics across this work include Ultrasound Imaging and Elastography (12 papers), AI in cancer detection (8 papers), Medical Image Segmentation Techniques (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Prostate Cancer Diagnosis and Treatment (4 papers), Ultrasonics and Acoustic Wave Propagation (3 papers), Robotics and Sensor-Based Localization (3 papers) and Ultrasound and Hyperthermia Applications (3 papers). The work is most often cited by research in Health Informatics (97 citations), Radiology, Nuclear Medicine and Imaging (467 citations), Artificial Intelligence (456 citations), Pulmonary and Respiratory Medicine (285 citations) and Computer Vision and Pattern Recognition (197 citations). Guy Nir has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Septimiu E. Salcudean, S. Larry Goldenberg, Ladan Fazli, Peter C. Black, Davood Karimi, Brian Skinnider, Carlos F. Villamil, Peyman Tavassoli, Dmitry A. Turbin and Davood Karimi. Their work appears in journals such as IEEE Transactions on Medical Imaging, International Journal of Computer Assisted Radiology and Surgery, NMR in Biomedicine, Journal of Contemporary Brachytherapy and JAMA Network Open.

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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