Sunil Verma
- Oncology top 0.1%
- HER2/EGFR in Cancer Research 59
- Cancer Treatment and Pharmacology 50
- Lung Cancer Research Studies 13
- Global Cancer Incidence and Screening 8
- Cancer Research top 0.5%
- Breast Cancer Treatment Studies 38
- Pulmonary and Respiratory Medicine top 0.2%
- Advanced Breast Cancer Therapies 49
- Lung Cancer Treatments and Mutations 16
- Genetics top 0.5%
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- Monoclonal and Polyclonal Antibodies Research 19
Sunil Verma
158 papers receiving 10.4k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Oncology 7.8k
- Cancer Research 2.5k
- Pulmonary and Respiratory Medicine 5.1k
- Genetics 1.2k
- Radiology, Nuclear Medicine and Imaging 2.1k
Countries citing papers authored by Sunil Verma
This map shows the geographic impact of Sunil Verma'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 Sunil Verma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sunil Verma more than expected).
Fields of papers citing papers by Sunil Verma
This network shows the impact of papers produced by Sunil Verma. 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 Sunil Verma. The network helps show where Sunil Verma may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sunil Verma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 1 | |
| 2 | 2020 | 0 | |
| 3 | 2018 | 105 | |
| 4 | 2018 | 32 | |
| 5 | 2017 | 9 | |
| 6 | 2017 | 99 | |
| 7 | 2017 | 6 | |
| 8 | 2017 | 5 | |
| 9 | 2017 | 3 | |
| 10 | 2016 | 150 | |
| 11 | Fulvestrant plus palbociclib versus fulvestrant plus placebo for treatment of hormone-receptor-positive, HER2-negative metastatic breast cancer that progressed on previous endocrine therapy (PALOMA-3): final analysis of the multicentre, double-blind, phase 3 randomised controlled trialbreakdown → | 2016 | 1247 |
| 12 | 2016 | 6 | |
| 13 | 2016 | 22 | |
| 14 | 2015 | 31 | |
| 15 | 2014 | 23 | |
| 16 | 2014 | 81 | |
| 17 | 2013 | 11 | |
| 18 | Trastuzumab Emtansine for HER2-Positive Advanced Breast Cancerbreakdown → | 2012 | 2665 |
| 19 | 2012 | 141 | |
| 20 | 2008 | 11 |
About Sunil Verma
Sunil Verma is a scholar working on Oncology, Cancer Research, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Internal Medicine, having authored 164 papers that have together received 10.6k indexed citations. Recurring topics across this work include HER2/EGFR in Cancer Research (59 papers), Cancer Treatment and Pharmacology (50 papers), Advanced Breast Cancer Therapies (49 papers), Breast Cancer Treatment Studies (38 papers), Monoclonal and Polyclonal Antibodies Research (19 papers), Lung Cancer Treatments and Mutations (16 papers), Lung Cancer Research Studies (13 papers) and Global Cancer Incidence and Screening (8 papers). The work is most often cited by research in Oncology (7.8k citations), Cancer Research (2.5k citations), Pulmonary and Respiratory Medicine (5.1k citations), Genetics (1.2k citations) and Radiology, Nuclear Medicine and Imaging (2.1k citations). Sunil Verma has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include Ian E. Krop, Mark D. Pegram, Véronique Dièras, David Miles, Luca Gianni, Manfred Welslau, Nadia Harbeck, Kim T. Blackwell, Jungsil Ro and Nicholas C. Turner. Their work appears in journals such as Journal of Clinical Oncology, Annals of Oncology, Cancer Research, The Oncologist and Breast Cancer Research and Treatment.
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.