Arvind Rao

850 total citations
21 papers, 594 citations indexed

About

Arvind Rao is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Radiation. According to data from OpenAlex, Arvind Rao has authored 21 papers receiving a total of 594 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Molecular Biology and 6 papers in Radiation. Recurrent topics in Arvind Rao's work include Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced Radiotherapy Techniques (6 papers) and Medical Imaging Techniques and Applications (4 papers). Arvind Rao is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (6 papers), Advanced Radiotherapy Techniques (6 papers) and Medical Imaging Techniques and Applications (4 papers). Arvind Rao collaborates with scholars based in United States, France and Sweden. Arvind Rao's co-authors include Shelli R. Kesler, Ingrid Oakley‐Girvan, Clifton D. Fuller, Douglas W. Blayney, Oxana Palesh, Meghan Karuturi, Christopher W. Woods, Laurence E. Court, Peter Woolf and Geoffrey S. Ginsburg and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and PLoS ONE.

In The Last Decade

Arvind Rao

20 papers receiving 586 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arvind Rao United States 10 225 115 114 111 80 21 594
Itay Barnea Israel 15 96 0.4× 196 1.7× 37 0.3× 64 0.6× 15 0.2× 40 951
Aiming Lu United States 19 662 2.9× 69 0.6× 131 1.1× 36 0.3× 45 0.6× 56 952
Mirabela Rusu United States 20 516 2.3× 173 1.5× 425 3.7× 39 0.4× 27 0.3× 84 1.2k
George A. Kastis Greece 15 514 2.3× 57 0.5× 100 0.9× 126 1.1× 25 0.3× 44 857
Chengyan Wang China 18 406 1.8× 222 1.9× 62 0.5× 19 0.2× 84 1.1× 74 1.0k
Juan Carlos López Alfonso Germany 17 178 0.8× 140 1.2× 113 1.0× 88 0.8× 39 0.5× 32 750
Michael G. Giacomelli United States 21 196 0.9× 213 1.9× 84 0.7× 33 0.3× 31 0.4× 55 1.0k
Matthew Fishburn Netherlands 13 163 0.7× 286 2.5× 14 0.1× 96 0.9× 48 0.6× 23 1.1k
Jan Lukas Robertus United Kingdom 13 140 0.6× 49 0.4× 148 1.3× 62 0.6× 41 0.5× 31 562
Zhi Chen China 21 597 2.7× 125 1.1× 249 2.2× 389 3.5× 168 2.1× 81 1.3k

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

20 of 20 papers shown
1.
2.
Yang, Guang, Arvind Rao, Christine Fernández-Maloigne, Vince D. Calhoun, & Gloria Menegaz. (2022). Explainable AI (XAI) In Biomedical Signal and Image Processing: Promises and Challenges. 2022 IEEE International Conference on Image Processing (ICIP). 1531–1535. 7 indexed citations
3.
Wang, Nicholas, Jeremy Kaplan, Joonsang Lee, et al.. (2021). Stress Testing Pathology Models with Generated Artifacts. Journal of Pathology Informatics. 12(1). 54–54. 7 indexed citations
4.
Rao, Arvind, et al.. (2020). Modular performance prediction for scientific workflows using Machine Learning. Future Generation Computer Systems. 114. 1–14. 3 indexed citations
5.
Cárdenas, Carlos, Rachel McCarroll, Laurence E. Court, et al.. (2018). Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function. International Journal of Radiation Oncology*Biology*Physics. 101(2). 468–478. 111 indexed citations
6.
Naqa, Issam El, Gilmer Valdés, André Dekker, et al.. (2018). Machine learning and modeling: Data, validation, communication challenges. Medical Physics. 45(10). e834–e840. 67 indexed citations
7.
Kesler, Shelli R., Arvind Rao, Douglas W. Blayney, et al.. (2017). Predicting Long-Term Cognitive Outcome Following Breast Cancer with Pre-Treatment Resting State fMRI and Random Forest Machine Learning. Frontiers in Human Neuroscience. 11. 555–555. 69 indexed citations
8.
Yang, Jinzhong, Beth M. Beadle, Richard E. Wendt, et al.. (2017). The feasibility of endoscopy-CT image registration in the head and neck without prospective endoscope tracking. PLoS ONE. 12(5). e0177886–e0177886. 4 indexed citations
9.
Rao, Arvind, et al.. (2017). A machine learning approach for modular workflow performance prediction. 1–11. 10 indexed citations
10.
Lehrer, Michael, Arvind Rao, Anindya Bhadra, et al.. (2017). Multiple-response regression analysis links magnetic resonance imaging features to de-regulated protein expression and pathway activity in lower grade glioma. Oncoscience. 4(5-6). 57–66. 7 indexed citations
11.
Yang, Jinzhong, Richard E. Wendt, Beth M. Beadle, et al.. (2017). The influence of non‐rigid anatomy and patient positioning on endoscopy‐CT image registration in the head and neck. Medical Physics. 44(8). 4159–4168. 3 indexed citations
12.
Lim, Tze Yee, Rajat J. Kudchadker, Jihong Wang, et al.. (2016). Effect of pulse sequence parameter selection on signal strength in positive‐contrast MRI markers for MRI‐based prostate postimplant assessment. Medical Physics. 43(7). 4312–4322. 13 indexed citations
13.
Bankson, James A., Christopher M. Walker, Marc S. Ramirez, et al.. (2015). Kinetic Modeling and Constrained Reconstruction of Hyperpolarized [1-13C]-Pyruvate Offers Improved Metabolic Imaging of Tumors. Cancer Research. 75(22). 4708–4717. 70 indexed citations
14.
Yock, Adam D., Arvind Rao, Lei Dong, et al.. (2014). Predicting oropharyngeal tumor volume throughout the course of radiation therapy from pretreatment computed tomography data using general linear models. Medical Physics. 41(5). 51705–51705. 4 indexed citations
15.
Lim, Tze Yee, R. Jason Stafford, Rajat J. Kudchadker, et al.. (2014). MRI characterization of cobalt dichloride-N-acetyl cysteine (C4) contrast agent marker for prostate brachytherapy. Physics in Medicine and Biology. 59(10). 2505–2516. 19 indexed citations
16.
Yock, Adam D., Arvind Rao, Lei Dong, et al.. (2014). Forecasting longitudinal changes in oropharyngeal tumor morphology throughout the course of head and neck radiation therapy. Medical Physics. 41(8Part1). 81708–81708. 4 indexed citations
17.
Huang, Yongsheng, Aimee K. Zaas, Arvind Rao, et al.. (2011). Temporal Dynamics of Host Molecular Responses Differentiate Symptomatic and Asymptomatic Influenza A Infection. PLoS Genetics. 7(8). e1002234–e1002234. 143 indexed citations
18.
19.
Rao, Arvind & Alfred O. Hero. (2011). Biological pathway inference using manifold embedding. 102. 5992–5995. 1 indexed citations
20.
Newberg, Justin Y., Jieyue Li, Arvind Rao, et al.. (2009). Automated analysis of Human Protein Atlas immunofluorescence images. PubMed. 5193229. 1023–1026. 20 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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