Varun Monga

2.5k citations
81 papers · 1.1k · h-index 19

Impact in

  • Genetics top 5%
    • Glioma Diagnosis and Treatment
  • Oncology top 10%
    • CAR-T cell therapy research
    • Vascular Tumors and Angiosarcomas
    • Cancer Immunotherapy and Biomarkers

Papers in

Varun Monga

78 papers receiving 1.1k citations

Peers

Varun Monga
Comparison fields: 5 of 94
  • Genetics 262
  • Oncology 372
  • Pulmonary and Respiratory Medicine 355
  • Cancer Research 134
  • Radiology, Nuclear Medicine and Imaging 171
Replace Terukazu Nakamura with:
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Varun Monga relative to Terukazu Nakamura Japan Terukazu Nakamura's profile →
Citations per field
00.5×7.8×
Terukazu Nakamura · 1×
Citations per year

Countries citing papers authored by Varun Monga

Since Specialization
Citations

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

Fields of papers citing papers by Varun Monga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020115
2 201853
3 202252
4 201748
5 202143
6 202043
7 202132
8 202032
9 201731
10 202131
11 201630
12 201730
13 202024
14 202122
15 202120
16 202119
17 202319
18 201819
19 202018
20 201917

About Varun Monga

Varun Monga is a scholar working on Oncology, Pulmonary and Respiratory Medicine, Molecular Biology, Genetics and Surgery, having authored 81 papers that have together received 1.1k indexed citations. Recurring topics across this work include Sarcoma Diagnosis and Treatment (26 papers), Glioma Diagnosis and Treatment (16 papers), Vascular Tumors and Angiosarcomas (10 papers), CAR-T cell therapy research (10 papers), Cancer Immunotherapy and Biomarkers (9 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), MRI in cancer diagnosis (6 papers) and Neuroblastoma Research and Treatments (6 papers). The work is most often cited by research in Genetics (262 citations), Oncology (372 citations), Pulmonary and Respiratory Medicine (355 citations), Cancer Research (134 citations) and Radiology, Nuclear Medicine and Imaging (171 citations). Varun Monga has collaborated with scholars based in United States, Australia and Canada. Frequent co-authors include Mohammed Milhem, Yousef Zakharia, Bryan G. Allen, Douglas R. Spitz, Munir R. Tanas, Sarah L. Mott, John M. Buatti, Prabhat C. Goswami, Caitlin Ward and Girish Bathla. Their work appears in journals such as Journal of Clinical Oncology, Cancers, Oncotarget, Journal of Adolescent and Young Adult Oncology and Scientific Reports.

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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