Tania Kaprealian

1.3k citations
71 papers · 944 indexed · h-index 18

Tania Kaprealian

68 papers receiving 933 citations

Peers

Tania Kaprealian
Comparison fields: 5 of 79
  • Radiation 285
  • Genetics 198
  • Neurology 266
  • Pulmonary and Respiratory Medicine 370
  • Epidemiology 321
Replace Zachary Seymour with:
Zachary Seymour United States
Yoshiko Oshiro Japan
Joshua H. Petit United States
Nadia N. Laack United States
Angelika Zabel Germany
Robert Corns United Kingdom
Barbara‐Ann Millar Canada
Atsuro Terahara Japan
Antonio Pontoriero Italy
Steven J. DiBiase United States
Tania Kaprealian relative to Zachary Seymour United States Zachary Seymour's profile →
Citations per field
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Citations per year

Countries citing papers authored by Tania Kaprealian

Since Specialization
Citations

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

Fields of papers citing papers by Tania Kaprealian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20230
2 202217
3 20225
4 202116
5 20211
6 20204
7 20203
8 202010
9 20195
10 20199
11 20191
12 20193
13 20199
14 201839
15 201848
16 201614
17 201612
18 201614
19 201616
20 20151

About Tania Kaprealian

Tania Kaprealian is a scholar working on Genetics, Radiation, Neurology, Pulmonary and Respiratory Medicine and Neurology, having authored 71 papers that have together received 944 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (28 papers), Meningioma and schwannoma management (21 papers), Brain Metastases and Treatment (15 papers), Advanced Radiotherapy Techniques (14 papers), Neurofibromatosis and Schwannoma Cases (10 papers), Vascular Malformations Diagnosis and Treatment (9 papers), Advanced MRI Techniques and Applications (6 papers) and Radiomics and Machine Learning in Medical Imaging (5 papers). The work is most often cited by research in Radiation (285 citations), Genetics (198 citations), Neurology (266 citations), Pulmonary and Respiratory Medicine (370 citations) and Epidemiology (321 citations). Tania Kaprealian has collaborated with scholars based in United States, Australia and Myanmar. Frequent co-authors include Stephen Tenn, Percy Lee, Isaac Yang, Ke Sheng, Nader Pouratian, Michael T. Selch, Robert Chin, Victoria Yu, Dan Nguyen and Alexander Gottschalk. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, World Neurosurgery, Journal of Neuro-Oncology, Advances in Radiation Oncology and Medical Physics.

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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