Sudha Rao

617 total citations
9 papers, 237 citations indexed

About

Sudha Rao is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence. According to data from OpenAlex, Sudha Rao has authored 9 papers receiving a total of 237 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Pulmonary and Respiratory Medicine, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Artificial Intelligence. Recurrent topics in Sudha Rao's work include Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (2 papers) and Medical Imaging and Pathology Studies (2 papers). Sudha Rao is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (2 papers), AI in cancer detection (2 papers) and Medical Imaging and Pathology Studies (2 papers). Sudha Rao collaborates with scholars based in United States, Netherlands and Austria. Sudha Rao's co-authors include Armando E. Fraire, Philip T. Cagle, Helmut Popper, Masuko Mori, Karl C. Podratz, Andrea Mariani, Timothy G. Lesnick, Maurice J. Webb, M. Peter Marinkovich and Bruce A. Woda and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Investigative Dermatology and Gynecologic Oncology.

In The Last Decade

Sudha Rao

9 papers receiving 228 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sudha Rao United States	7	98	58	48	37	34	9	237
Derk H. Rutgers Netherlands	8	91 0.9×	85 1.5×	93 1.9×	16 0.4×	82 2.4×	11	276
Claudia Martins Canada	8	37 0.4×	145 2.5×	92 1.9×	47 1.3×	97 2.9×	10	358
G. Feichter Germany	9	40 0.4×	38 0.7×	75 1.6×	35 0.9×	63 1.9×	27	277
John M. Esposito United States	8	106 1.1×	109 1.9×	64 1.3×	64 1.7×	18 0.5×	17	382
M. Kiechle‐Schwarz Germany	12	38 0.4×	102 1.8×	97 2.0×	54 1.5×	74 2.2×	23	319
C. Griso Italy	9	117 1.2×	72 1.2×	78 1.6×	9 0.2×	19 0.6×	18	331
Iris Halfpenny United Kingdom	9	28 0.3×	59 1.0×	66 1.4×	17 0.5×	75 2.2×	11	424
A.A.M. van der Wurff Netherlands	14	63 0.6×	93 1.6×	77 1.6×	125 3.4×	101 3.0×	24	348
Meredith Stevers United States	5	87 0.9×	101 1.7×	78 1.6×	6 0.2×	15 0.4×	7	295
Ana Montes United Kingdom	11	25 0.3×	56 1.0×	86 1.8×	20 0.5×	72 2.1×	31	236

Countries citing papers authored by Sudha Rao

Since Specialization

Citations

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

Fields of papers citing papers by Sudha Rao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sudha Rao

This figure shows the co-authorship network connecting the top 25 collaborators of Sudha Rao. A scholar is included among the top collaborators of Sudha 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 Sudha Rao. Sudha 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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9 of 9 papers shown

Wong, Pok Fai, Charles Santori, Andrew Homyk, et al.. (2024). Clinical-Grade Validation of an Autofluorescence Virtual Staining System With Human Experts and a Deep Learning System for Prostate Cancer. Modern Pathology. 37(11). 100573–100573. 4 indexed citations

Glass, Benjamin, Michel E. Vandenberghe, Marlon C. Rebelatto, et al.. (2021). Machine learning models to quantify HER2 for real-time tissue image analysis in prospective clinical trials.. Journal of Clinical Oncology. 39(15_suppl). 3061–3061. 4 indexed citations

Mori, Masuko, Sudha Rao, Helmut Popper, Philip T. Cagle, & Armando E. Fraire. (2001). Atypical Adenomatous Hyperplasia of the Lung: A Probable Forerunner in the Development of Adenocarcinoma of the Lung. Modern Pathology. 14(2). 72–84. 101 indexed citations

Mariani, Andrea, Maurice J. Webb, Sudha Rao, Timothy G. Lesnick, & Karl C. Podratz. (2001). Significance of Pathologic Patterns of Pelvic Lymph Node Metastases in Endometrial Cancer. Gynecologic Oncology. 80(2). 113–120. 39 indexed citations

Scott, Glynis, et al.. (1999). Melanocytes adhere to and synthesize laminin‐5 in vitro. Experimental Dermatology. 8(3). 212–221. 12 indexed citations

Marinkovich, M. Peter, Sudha Rao, George J. Giudice, et al.. (1997). LAD-1 Is Absent in a Subset of Junctional Epidermolysis Bullosa Patients. Journal of Investigative Dermatology. 109(3). 356–359. 22 indexed citations

Rao, Sudha, Murli Krishna, Bruce A. Woda, Louis Savas, & Armando E. Fraire. (1996). Immunohistochemical detection of bcl-2 protein in adenocarcinoma and Non-Neoplastic cellular compartments of the lung. Lung Cancer. 16(1). 111–111. 14 indexed citations

Rao, Sudha, et al.. (1995). Alveolar cell hyperplasia in association with adenocarcinoma of lung. Lung Cancer. 13(1). 86–86. 27 indexed citations

Potocki, Lorraine, et al.. (1994). Tetrasomy 21 in megakaryoblastic leukemia. Cancer Genetics and Cytogenetics. 74(1). 66–70. 14 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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