Sujata V. Ghate

1.3k total citations
38 papers, 858 citations indexed

About

Sujata V. Ghate is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sujata V. Ghate has authored 38 papers receiving a total of 858 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 18 papers in Radiology, Nuclear Medicine and Imaging and 16 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sujata V. Ghate's work include AI in cancer detection (20 papers), Digital Radiography and Breast Imaging (16 papers) and Breast Lesions and Carcinomas (10 papers). Sujata V. Ghate is often cited by papers focused on AI in cancer detection (20 papers), Digital Radiography and Breast Imaging (16 papers) and Breast Lesions and Carcinomas (10 papers). Sujata V. Ghate collaborates with scholars based in United States, China and Switzerland. Sujata V. Ghate's co-authors include Jay A. Baker, Maciej A. Mazurowski, Ruth Walsh, Ashirbani Saha, Lars J. Grimm, Mary Scott Soo, Manisha Bahl, Michael R. Harowicz, Connie E. Kim and Joseph Y. Lo and has published in prestigious journals such as Radiology, British Journal of Cancer and IEEE Transactions on Medical Imaging.

In The Last Decade

Sujata V. Ghate

35 papers receiving 842 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sujata V. Ghate United States 17 521 402 253 184 137 38 858
Luca Alessandro Carbonaro Italy 18 639 1.2× 197 0.5× 220 0.9× 232 1.3× 95 0.7× 47 902
Karin Leifland Sweden 19 292 0.6× 413 1.0× 437 1.7× 309 1.7× 383 2.8× 30 981
Christiane Marx Germany 14 381 0.7× 146 0.4× 127 0.5× 187 1.0× 109 0.8× 18 656
Jocelyn A. Rapelyea United States 16 676 1.3× 320 0.8× 463 1.8× 494 2.7× 257 1.9× 30 1.2k
Mary Rickard Australia 17 253 0.5× 359 0.9× 350 1.4× 153 0.8× 378 2.8× 60 882
Ralph Wynn United States 16 517 1.0× 394 1.0× 238 0.9× 484 2.6× 199 1.5× 28 1.1k
Jessica Torrente United States 9 342 0.7× 279 0.7× 265 1.0× 260 1.4× 169 1.2× 10 671
Linda Hovanessian‐Larsen United States 13 439 0.8× 122 0.3× 208 0.8× 269 1.5× 192 1.4× 36 845
Belinda Curpen Canada 17 478 0.9× 274 0.7× 85 0.3× 161 0.9× 205 1.5× 49 837
Amy Lu United States 10 393 0.8× 491 1.2× 436 1.7× 87 0.5× 132 1.0× 21 724

Countries citing papers authored by Sujata V. Ghate

Since Specialization
Citations

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

Fields of papers citing papers by Sujata V. Ghate

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sujata V. Ghate. 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 Sujata V. Ghate. The network helps show where Sujata V. Ghate may publish in the future.

Co-authorship network of co-authors of Sujata V. Ghate

This figure shows the co-authorship network connecting the top 25 collaborators of Sujata V. Ghate. A scholar is included among the top collaborators of Sujata V. Ghate 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 Sujata V. Ghate. Sujata V. Ghate 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.
Ghate, Sujata V., et al.. (2024). Feasibility of Prospective Assignment of Initial Method of Detection of Breast Cancer: A Multicenter Pilot Study. Journal of the American College of Radiology. 21(7). 1001–1009. 3 indexed citations
2.
Huang, Yu, Roberto Lo Gullo, Mary Hughes, et al.. (2024). Cross-site Validation of AI Segmentation and Harmonization in Breast MRI. Journal of Imaging Informatics in Medicine. 38(3). 1642–1652.
3.
Patel, Maitray D., Mindy M. Horrow, Aya Kamaya, et al.. (2020). Mapping the Ultrasound Landscape to Define Point-of-Care Ultrasound and Diagnostic Ultrasound: A Proposal From the Society of Radiologists in Ultrasound and ACR Commission on Ultrasound. Journal of the American College of Radiology. 18(1). 42–52. 16 indexed citations
4.
Hou, Rui, Jay A. Baker, Sora C. Yoon, et al.. (2020). Predicting Upstaging of DCIS to Invasive Disease: Radiologists's Predictive Performance. Academic Radiology. 27(11). 1580–1585. 6 indexed citations
5.
6.
Saha, Ashirbani, Michael R. Harowicz, Lars J. Grimm, et al.. (2018). A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features. British Journal of Cancer. 119(4). 508–516. 187 indexed citations
7.
Grimm, Lars J., Ashirbani Saha, Sujata V. Ghate, et al.. (2018). Relationship between Background Parenchymal Enhancement on High-risk Screening MRI and Future Breast Cancer Risk. Academic Radiology. 26(1). 69–75. 39 indexed citations
8.
Saha, Ashirbani, Jun Zhang, Sujata V. Ghate, et al.. (2018). Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis. 23. 102–102. 4 indexed citations
9.
Saha, Ashirbani, Lars J. Grimm, Michael R. Harowicz, et al.. (2016). Interobserver variability in identification of breast tumors in MRI and its implications for prognostic biomarkers and radiogenomics. Medical Physics. 43(8Part1). 4558–4564. 24 indexed citations
10.
11.
Mazurowski, Maciej A., Lars J. Grimm, Jing Zhang, et al.. (2015). Recurrence-free survival in breast cancer is associated with MRI tumor enhancement dynamics quantified using computer algorithms. European Journal of Radiology. 84(11). 2117–2122. 27 indexed citations
12.
Ikejimba, Lynda C., et al.. (2014). Task-based strategy for optimized contrast enhanced breast imaging: Analysis of six imaging techniques for mammography and tomosynthesis. Medical Physics. 41(6Part1). 61908–61908. 23 indexed citations
13.
14.
Ikejimba, Lynda C., Yuan Lin, Baiyu Chen, et al.. (2012). Task-based strategy for optimized contrast enhanced breast imaging: analysis of six imaging techniques for mammography and tomosynthesis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8313. 831309–831309. 5 indexed citations
15.
Ghate, Sujata V., Jay A. Baker, Ashley Hawkins, & Brian J. Soher. (2011). Titanium vs Carbon Coated Ceramic Breast Tissue Marker Clips:. Academic Radiology. 18(6). 770–773. 13 indexed citations
16.
Ghate, Sujata V., et al.. (2010). Is Surgical Excision of Core Biopsy Proven Benign Papillomas of the Breast Necessary?. Academic Radiology. 17(5). 553–557. 40 indexed citations
17.
Wilke, Lee G., Gloria Broadwater, Elizabeth B. Owens, et al.. (2009). Breast self-examination: defining a cohort still in need. The American Journal of Surgery. 198(4). 575–579. 30 indexed citations
18.
Samei, Ehsan, Amarpreet S. Chawla, Jay A. Baker, et al.. (2009). The Influence of Increased Ambient Lighting on Mass Detection in Mammograms. Academic Radiology. 16(3). 299–304. 10 indexed citations
19.
20.
Soo, Mary Scott, Sujata V. Ghate, & David M. DeLong. (1999). Stereotactic biopsy of noncalcified breast lesions. Clinical Imaging. 23(6). 347–352. 7 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Luca Alessandro Carbonaro Breakdown of academic impact, for papers by Karin Leifland Breakdown of academic impact, for papers by Christiane Marx Breakdown of academic impact, for papers by Jocelyn A. Rapelyea Breakdown of academic impact, for papers by Mary Rickard Breakdown of academic impact, for papers by Ralph Wynn Breakdown of academic impact, for papers by Jessica Torrente Breakdown of academic impact, for papers by Linda Hovanessian‐Larsen Breakdown of academic impact, for papers by Belinda Curpen Breakdown of academic impact, for papers by Amy Lu
Rankless by CCL
2026