Tal Zeevi

37 papers receiving 440 citations

Peers

Tal Zeevi
Comparison fields: 5 of 66
  • Health Informatics 39
  • Otorhinolaryngology 68
  • Radiology, Nuclear Medicine and Imaging 276
  • Occupational Therapy 44
  • Hepatology 55
Replace Sungwon Ham with:
Sungwon Ham South Korea
Stefan P. Haider United States
Jason Cai United States
Zhenyu Shu China
Halit Nahit Şendur Türkiye
Arunnit Boonrod Thailand
Guangying Ruan China
Thomas Weißmann Germany
Jiliang Ren China
Tal Zeevi relative to Sungwon Ham South Korea Sungwon Ham's profile →
Citations per field
00.5×11×
Sungwon Ham · 1×
Citations per year

Countries citing papers authored by Tal Zeevi

Since Specialization
Citations

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

Fields of papers citing papers by Tal Zeevi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202053
2 201749
3 202049
4 202028
5 202224
6 202222
7 202122
8 202220
9 202419
10 202314
11 202313
12 202412
13 202212
14 202012
15 202212
16 202210
17 20229
18 20159
19 20259
20 20217

About Tal Zeevi

Tal Zeevi is a scholar working on Radiology, Nuclear Medicine and Imaging, Epidemiology, Hepatology, Pulmonary and Respiratory Medicine and Neurology, having authored 47 papers that have together received 441 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (32 papers), Acute Ischemic Stroke Management (11 papers), Hepatocellular Carcinoma Treatment and Prognosis (10 papers), Brain Tumor Detection and Classification (7 papers), Intracerebral and Subarachnoid Hemorrhage Research (7 papers), MRI in cancer diagnosis (5 papers), Medical Imaging Techniques and Applications (4 papers) and Artificial Intelligence in Healthcare and Education (4 papers). The work is most often cited by research in Health Informatics (39 citations), Otorhinolaryngology (68 citations), Radiology, Nuclear Medicine and Imaging (276 citations), Occupational Therapy (44 citations) and Hepatology (55 citations). Tal Zeevi has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Seyedmehdi Payabvash, Stefan P. Haider, Amit Mahajan, Neima Brauner, Ayelet Levy, Amit Gefen, Philipp Baumeister, Benjamin L. Judson, Benjamin H. Kann and Manju L. Prasad. Their work appears in journals such as European Radiology, Cancers, American Journal of Neuroradiology, Journal of Vascular and Interventional Radiology and Neuro-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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