Arvind Rao

42.6k total citations · 2 hit papers
131 papers, 4.0k citations indexed

About

Arvind Rao is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Arvind Rao has authored 131 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 43 papers in Radiology, Nuclear Medicine and Imaging and 40 papers in Oncology. Recurrent topics in Arvind Rao's work include Radiomics and Machine Learning in Medical Imaging (38 papers), Glioma Diagnosis and Treatment (30 papers) and Gene expression and cancer classification (15 papers). Arvind Rao is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (38 papers), Glioma Diagnosis and Treatment (30 papers) and Gene expression and cancer classification (15 papers). Arvind Rao collaborates with scholars based in United States, Japan and United Kingdom. Arvind Rao's co-authors include Ganesh Rao, Dalu Yang, Souptik Barua, Julienne L. Carstens, Raghu Kalluri, Pedro Corrêa de Sampaio, Valerie S. LeBleu, Huamin Wang, James P. Allison and Martin Vallières and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Arvind Rao

121 papers receiving 3.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Spatial computation of intratumoral T cells correlates with survival of patients with pancreatic cancer

2017 434 citations Dalu Yang, Arvind Rao et al. profile →
Machine and deep learning methods for radiomics

2020 360 citations Arvind Rao et al. Medical Physics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Arvind Rao United States	32	1.5k	1.4k	884	761	737	131	4.0k
Dongsheng Gu China	37	2.1k 1.4×	867 0.6×	901 1.0×	905 1.2×	389 0.5×	106	4.2k
Lee Cooper United States	34	1.5k 1.0×	655 0.5×	1.1k 1.2×	469 0.6×	811 1.1×	117	4.4k
Niels Grabe Germany	33	606 0.4×	1.7k 1.2×	1.2k 1.4×	626 0.8×	196 0.3×	106	4.6k
Antje Wick Germany	32	1.5k 1.0×	1.1k 0.8×	994 1.1×	975 1.3×	2.7k 3.7×	87	4.6k
Raymond Y. Huang United States	30	2.5k 1.6×	766 0.6×	556 0.6×	1.1k 1.5×	1.7k 2.2×	122	4.8k
Rivka R. Colen United States	34	2.1k 1.4×	535 0.4×	450 0.5×	915 1.2×	1.4k 1.8×	138	4.2k
Tetsuya Higuchi Japan	30	896 0.6×	896 0.6×	880 1.0×	614 0.8×	177 0.2×	181	3.8k
Ganesh Rao United States	47	1.2k 0.8×	1.2k 0.8×	1.4k 1.5×	1.3k 1.7×	2.2k 3.0×	193	6.7k
Olivier Gevaert United States	47	3.3k 2.2×	1.0k 0.7×	2.1k 2.3×	2.0k 2.6×	909 1.2×	180	7.6k
Jongphil Kim United States	32	1.2k 0.8×	914 0.7×	610 0.7×	1.1k 1.4×	153 0.2×	173	3.6k

Countries citing papers authored by Arvind Rao

Since Specialization

Citations

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

Fields of papers citing papers by Arvind Rao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arvind Rao

This figure shows the co-authorship network connecting the top 25 collaborators of Arvind Rao. A scholar is included among the top collaborators of Arvind Rao 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 Arvind Rao. Arvind Rao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Turkestani, Najla Al, Lucía Cevidanes, Jonas Bianchi, et al.. (2025). Interpretable machine learning integrates multi-source biomarkers for osteoarthritis diagnosis and mechanistic insights: A temporomandibular joint model. Osteoarthritis and Cartilage. 33(12). 1522–1533.

Patel, Parth, David Scoville, Brittney Cotta, et al.. (2024). Spatial Transcriptomic Profiling to Characterize the Nature of Peripheral- Versus Transition-zone Prostate Cancer. European Urology Focus. 11(2). 226–234. 3 indexed citations

Jiang, Long, Weiwei Wang, Amanda K. Huber, et al.. (2024). Potentiating the radiation-induced type I interferon anti-tumoral immune response by ATM inhibition in pancreatic cancer. JCI Insight. 9(6). 7 indexed citations

Turkestani, Najla Al, Tengfei Li, Jonas Bianchi, et al.. (2024). A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression. Proceedings of the National Academy of Sciences. 121(8). e2306132121–e2306132121. 6 indexed citations

Malgulwar, Prit Benny, Carla Danussi, W. Evan Johnson, et al.. (2023). Sirtuin 2 inhibition modulates chromatin landscapes genome-wide to induce senescence in ATRX-deficient malignant glioma. Neuro-Oncology. 26(1). 55–67. 10 indexed citations

Ravikumar, Visweswaran, Tong Xu, Wajd N. Al‐Holou, Salar Fattahi, & Arvind Rao. (2023). Efficient Inference of Spatially-Varying Gaussian Markov Random Fields With Applications in Gene Regulatory Networks. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(5). 2920–2932.

Waljee, Akbar K., Eileen M Weinheimer-Haus, Amina Abubakar, et al.. (2022). Artificial intelligence and machine learning for early detection and diagnosis of colorectal cancer in sub-Saharan Africa. Gut. 71(7). 1259–1265. 35 indexed citations

Stossi, Fabio, Pankaj K. Singh, Hannah L. Johnson, et al.. (2022). Quality Control for Single Cell Imaging Analytics Using Endocrine Disruptor-Induced Changes in Estrogen Receptor Expression. Environmental Health Perspectives. 130(2). 27008–27008. 7 indexed citations

Türk, Sevcan, Nicholas Wang, Shariq Mohammed, et al.. (2022). Comparative study of radiologists vs machine learning in differentiating biopsy-proven pseudoprogression and true progression in diffuse gliomas. SHILAP Revista de lepidopterología. 2(3). 100088–100088. 3 indexed citations

10.

Wang, Xiangmeng, Po Yee Mak, Hong Mu, et al.. (2020). Combinatorial Inhibition of Focal Adhesion Kinase and BCL-2 Enhances Antileukemia Activity of Venetoclax in Acute Myeloid Leukemia. Molecular Cancer Therapeutics. 19(8). 1636–1648. 13 indexed citations

11.

Gupta, Rajarsi, Le Hou, Shahira Abousamra, et al.. (2020). Utilizing Automated Breast Cancer Detection to Identify Spatial Distributions of Tumor-Infiltrating Lymphocytes in Invasive Breast Cancer. American Journal Of Pathology. 190(7). 1491–1504. 73 indexed citations

12.

Ishizawa, Jo, Kenji Nakamaru, Takahiko Seki, et al.. (2018). Predictive Gene Signatures Determine Tumor Sensitivity to MDM2 Inhibition. Cancer Research. 78(10). 2721–2731. 44 indexed citations

13.

Bambhroliya, Arvind, Bisrat G. Debeb, Jay P. Reddy, et al.. (2018). Gene set analysis of post-lactational mammary gland involution gene signatures in inflammatory and triple-negative breast cancer. PLoS ONE. 13(4). e0192689–e0192689. 18 indexed citations

14.

Krafft, Shane P., Arvind Rao, Francesco C. Stingo, et al.. (2018). The utility of quantitativeCTradiomics features for improved prediction of radiation pneumonitis. Medical Physics. 45(11). 5317–5324. 97 indexed citations

15.

Moriguchi, Takashi, Tomofumi Hoshino, Arvind Rao, et al.. (2018). A Gata3 3′ Distal Otic Vesicle Enhancer Directs Inner Ear-Specific Gata3 Expression. Molecular and Cellular Biology. 38(21). 9 indexed citations

16.

Sutton, Elizabeth J., Erich P. Huang, Karen Drukker, et al.. (2017). Breast MRI radiomics: comparison of computer- and human-extracted imaging phenotypes. European Radiology Experimental. 1(1). 22–22. 27 indexed citations

17.

Rao, Arvind, et al.. (2016). Integrative Analysis of mRNA, microRNA, and Protein Correlates of Relative Cerebral Blood Volume Values in GBM Reveals the Role for Modulators of Angiogenesis and Tumor Proliferation. SHILAP Revista de lepidopterología.

18.

Yang, Dalu, et al.. (2015). Evaluation of tumor‐derived MRI‐texture features for discrimination of molecular subtypes and prediction of 12‐month survival status in glioblastoma. Medical Physics. 42(11). 6725–6735. 114 indexed citations

19.

Rao, Arvind, Alfred O. Hero, David J. States, & James Douglas Engel. (2007). Motif Discovery in Tissue-Specific Regulatory Sequences Using Directed Information. PubMed. 2007. 1–13. 15 indexed citations

20.

Hasegawa, Susan L., Takashi Moriguchi, Arvind Rao, et al.. (2006). Dosage-dependent rescue of definitive nephrogenesis by a distant Gata3 enhancer. Developmental Biology. 301(2). 568–577. 30 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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