Dimple Pandya

1.1k total citations
12 papers, 175 citations indexed

About

Dimple Pandya is a scholar working on Oncology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Dimple Pandya has authored 12 papers receiving a total of 175 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Oncology, 5 papers in Radiology, Nuclear Medicine and Imaging and 4 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Dimple Pandya's work include Cancer Immunotherapy and Biomarkers (10 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Cancer Genomics and Diagnostics (3 papers). Dimple Pandya is often cited by papers focused on Cancer Immunotherapy and Biomarkers (10 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and Cancer Genomics and Diagnostics (3 papers). Dimple Pandya collaborates with scholars based in United States, Sweden and Italy. Dimple Pandya's co-authors include Robin Edwards, Emily Prince, Jenine K. Sanzari, Han Chang, Zachary Boyd, Yelena Y. Janjigian, Filippo de Braud, Christopher Harbison, Teresa Sánchez and Nathan O. Siemers and has published in prestigious journals such as Journal of Clinical Oncology, Cancer Research and Clinical Cancer Research.

In The Last Decade

Dimple Pandya

11 papers receiving 174 citations

Peers

Dimple Pandya
Mojca Unk Slovenia
Kees Bisschop Netherlands
Fabien Gaire Germany
Lindsay C. Hewitt United Kingdom
Dimple Pandya
Citations per year, relative to Dimple Pandya Dimple Pandya (= 1×) peers Minori Koshiji Rosales

Countries citing papers authored by Dimple Pandya

Since Specialization
Citations

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

Fields of papers citing papers by Dimple Pandya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dimple Pandya

This figure shows the co-authorship network connecting the top 25 collaborators of Dimple Pandya. A scholar is included among the top collaborators of Dimple Pandya based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dimple Pandya. Dimple Pandya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

12 of 12 papers shown
1.
3.
Lei, Ming, Nathan O. Siemers, Dimple Pandya, et al.. (2021). Analyses of PD-L1 and Inflammatory Gene Expression Association with Efficacy of Nivolumab ± Ipilimumab in Gastric Cancer/Gastroesophageal Junction Cancer. Clinical Cancer Research. 27(14). 3926–3935. 57 indexed citations
4.
Prince, Emily, et al.. (2021). Analytical Concordance of PD-L1 Assays Utilizing Antibodies From FDA-Approved Diagnostics in Advanced Cancers: A Systematic Literature Review. JCO Precision Oncology. 5(5). 953–973. 39 indexed citations
5.
Li, Bin, Lloye M. Dillon, Jennifer L. Jones, et al.. (2020). A comparative study of PD-L1 IHC assays using immune cell scoring and CPS in breast cancer.. Journal of Clinical Oncology. 38(15_suppl). e15262–e15262. 3 indexed citations
6.
Montalto, Michael, George Lee, Dimple Pandya, et al.. (2020). Abstract 2017: Association of digital and manual quantification of tumor PD-L1 expression with outcomes in nivolumab-treated patients. Cancer Research. 80(16_Supplement). 2017–2017. 3 indexed citations
7.
Szabó, Péter M., George Lee, Scott Ely, et al.. (2019). CD8+ T cells in tumor parenchyma and stroma by image analysis (IA) and gene expression profiling (GEP): Potential biomarkers for immuno-oncology (I-O) therapy.. Journal of Clinical Oncology. 37(15_suppl). 2594–2594. 4 indexed citations
8.
Lei, Ming, Nathan O. Siemers, Dimple Pandya, et al.. (2019). Abstract 2673: Association of PD-L1 combined positive score and immune gene signatures with efficacy of nivolumab (NIVO) ± ipilimumab (IPI) in patients with metastatic gastroesophageal cancer (mGEC). Cancer Research. 79(13_Supplement). 2673–2673. 12 indexed citations
10.
Carleton, Michael, Janine Powers, Penny Phillips, et al.. (2018). Pharmacodynamics (PD) and genomic profiling of pts treated with cabiralizumab (cabira) + nivolumab (NIVO) provide evidence of on-target tumor immune modulations and support future clinical applications.. Journal of Clinical Oncology. 36(15_suppl). 3020–3020. 11 indexed citations
11.
Hussein, Maen, Donald Richards, Brian Ulrich, et al.. (2016). ORAL01.02: Biopsies in Initial Diagnosis of Non–Small Cell Lung Cancer in US Community Oncology Practices: Implications for First-Line Immunotherapy. Journal of Thoracic Oncology. 11(11). S249–S250. 2 indexed citations
12.
Iida, Shinsuke, Hirokazu Nagai, Michael Robbins, et al.. (2016). Elotuzumab with lenalidomide and dexamethasone for Japanese patients with relapsed/refractory multiple myeloma: phase 1 study. International Journal of Hematology. 105(3). 326–334. 6 indexed citations

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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