Bhavika Patel

2.8k total citations
93 papers, 1.8k citations indexed

About

Bhavika Patel is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Bhavika Patel has authored 93 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Pulmonary and Respiratory Medicine, 42 papers in Radiology, Nuclear Medicine and Imaging and 30 papers in Oncology. Recurrent topics in Bhavika Patel's work include Digital Radiography and Breast Imaging (43 papers), Global Cancer Incidence and Screening (27 papers) and Breast Cancer Treatment Studies (24 papers). Bhavika Patel is often cited by papers focused on Digital Radiography and Breast Imaging (43 papers), Global Cancer Incidence and Screening (27 papers) and Breast Cancer Treatment Studies (24 papers). Bhavika Patel collaborates with scholars based in United States, United Kingdom and Netherlands. Bhavika Patel's co-authors include Barbara A. Pockaj, Teresa Wu, Heidi Kosiorek, John Lewin, Richard J. Gray, M. Lobbes, Victor J. Pizzitola, Bin Zheng, Jing Li and Donald W. Northfelt and has published in prestigious journals such as Journal of Clinical Oncology, Cell Metabolism and Cancer.

In The Last Decade

Bhavika Patel

88 papers receiving 1.8k citations

Peers

Bhavika Patel

RNMI

PRM

ONCOL

Min Sun Bae South Korea

Jeroen Veltman Netherlands

Haydee Ojeda‐Fournier United States

Christopher Comstock United States

Paola Clauser Austria

Won Hwa Kim South Korea

Kathy Schilling United States

Regina J. Hooley United States

Lora D. Barke United States

Christopher Abbosh United Kingdom

Min Sun Bae South Korea

Bhavika Patel

1.2k ×1.2

RNMI

338 ×0.4

PRM

562 ×1.0

503 ×0.9

291 ×0.8

ONCOL

Citations per year, relative to Bhavika Patel Bhavika Patel (= 1×) peers Min Sun Bae

Countries citing papers authored by Bhavika Patel

Since Specialization

Citations

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

Fields of papers citing papers by Bhavika Patel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bhavika Patel

This figure shows the co-authorship network connecting the top 25 collaborators of Bhavika Patel. A scholar is included among the top collaborators of Bhavika Patel 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 Bhavika Patel. Bhavika Patel 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

Zuley, Margarita L., Richard E. Sharpe, Victor J. Pizzitola, et al.. (2025). Relative Costs and Outcomes of a Contrast-Enhanced Mammography-Guided Biopsy Trial. Journal of Breast Imaging. 7(5). 541–550. 1 indexed citations

Souadka, Amine, Bhavik N. Patel, Nada Sbihi, et al.. (2023). Evolution of Breast Cancer Recurrence Risk Prediction: A Systematic Review of Statistical and Machine Learning–Based Models. JCO Clinical Cancer Informatics. 7(7). e2300049–e2300049. 11 indexed citations

Patel, Bhavika, et al.. (2023). How to Recognize and Correct Artifacts on Contrast-Enhanced Mammography. Journal of Breast Imaging. 5(4). 486–497. 3 indexed citations

Sharpe, Richard E., et al.. (2023). False-Positive and False-Negative Contrast-enhanced Mammograms: Pitfalls and Strategies to Improve Cancer Detection. Radiographics. 43(12). e230100–e230100. 7 indexed citations

Lloyd, Maxwell R., et al.. (2023). Artificial intelligence for triaging of breast cancer screening mammograms and workload reduction: A meta-analysis of a deep learning software. Journal of Medical Screening. 31(3). 157–165. 8 indexed citations

Patel, Bhavika, et al.. (2023). Imaging Characteristics of and Multidisciplinary Management Considerations for Atypical Ductal Hyperplasia and Flat Epithelial Atypia: Review of Current Literature. Radiographics. 43(10). e230016–e230016. 4 indexed citations

Scott, Ryan P., Richard E. Sharpe, Gina L. Mazza, et al.. (2022). Contrast Enhanced Mammography in Routine Clinical Practice: Frequency and Malignancy Rates of Enhancing Otherwise Occult Findings. Clinical Breast Cancer. 22(7). e736–e744. 6 indexed citations

Patel, Bhavika, Kay Pepin, Kathy R. Brandt, et al.. (2022). Association of breast cancer risk, density, and stiffness: global tissue stiffness on breast MR elastography (MRE). Breast Cancer Research and Treatment. 194(1). 79–89. 20 indexed citations

Patel, Bhavika, et al.. (2022). The Dense Breast Clinic: Initial Experience of a Patient-Centered Breast Imaging Clinic. Journal of Breast Imaging. 4(6). 582–589. 3 indexed citations

10.

Christensen, Eric, et al.. (2022). Relationship between Race and Access to Newer Mammographic Technology in Women with Medicare Insurance. Radiology. 306(2). e221153–e221153. 14 indexed citations

11.

Sensakovic, William F., et al.. (2021). Contrast-enhanced Mammography: How Does It Work?. Radiographics. 41(3). 829–839. 23 indexed citations

12.

Ridgeway, Jennifer L., Sarah M. Jenkins, Bijan J. Borah, et al.. (2021). Evaluating educational interventions to increase breast density awareness among Latinas: A randomized trial in a Federally Qualified Health Center. Cancer. 128(5). 1038–1047. 7 indexed citations

13.

Schwartz, Michael, et al.. (2020). Reducing Errors in Radiology Specimen Labeling Through Use of a Two-person Check. Current Problems in Diagnostic Radiology. 49(5). 351–354.

14.

Patel, Bhavika, Naziya Samreen, Yuxiang Zhou, et al.. (2020). MR Elastography of the Breast: Evolution of Technique, Case Examples, and Future Directions. Clinical Breast Cancer. 21(1). e102–e111. 23 indexed citations

15.

Gray, Richard J., Nabil Wasif, Patricia A. Cronin, et al.. (2019). Predictive factors of upstaging DCIS to invasive carcinoma in BCT vs mastectomy. The American Journal of Surgery. 217(6). 1025–1029. 11 indexed citations

16.

McDonald, Bradon R., Tania Contente‐Cuomo, Stephen‐John Sammut, et al.. (2019). Personalized circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer. Science Translational Medicine. 11(504). 201 indexed citations

17.

Hilal, Talal, Matthew F. Covington, Heidi Kosiorek, et al.. (2018). Breast MRI phenotype and background parenchymal enhancement may predict tumor response to neoadjuvant endocrine therapy. The Breast Journal. 24(6). 1010–1014. 20 indexed citations

18.

Gao, Fei, Teresa Wu, Jing Li, et al.. (2018). SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis. Computerized Medical Imaging and Graphics. 70. 53–62. 152 indexed citations

19.

Pockaj, Barbara A., Nabil Wasif, Victor J. Pizzitola, et al.. (2017). Operative outcomes of conventional specimen radiography versus in-operating room specimen radiography in radioactive seed-localized segmental mastectomies. The American Journal of Surgery. 215(1). 151–154. 7 indexed citations

20.

Patel, Bhavika, et al.. (2017). Clinical utility of contrast-enhanced spectral mammography as an adjunct for tomosynthesis-detected architectural distortion. Clinical Imaging. 46. 44–52. 48 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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