Sora C. Yoon

1.6k total citations
42 papers, 1.2k citations indexed

About

Sora C. Yoon is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine and Artificial Intelligence. According to data from OpenAlex, Sora C. Yoon has authored 42 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Pathology and Forensic Medicine and 10 papers in Artificial Intelligence. Recurrent topics in Sora C. Yoon's work include Radiology practices and education (11 papers), AI in cancer detection (10 papers) and Breast Lesions and Carcinomas (10 papers). Sora C. Yoon is often cited by papers focused on Radiology practices and education (11 papers), AI in cancer detection (10 papers) and Breast Lesions and Carcinomas (10 papers). Sora C. Yoon collaborates with scholars based in United States, South Korea and Canada. Sora C. Yoon's co-authors include Lars J. Grimm, Maciej A. Mazurowski, Mary Scott Soo, Connie Kim, Sujata V. Ghate, Jing Zhang, Karen S. Johnson, Jay A. Baker, James C. Campbell and Rebecca A. Shelby and has published in prestigious journals such as Radiology, Spine and American Journal of Roentgenology.

In The Last Decade

Sora C. Yoon

39 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sora C. Yoon United States 20 742 218 195 192 175 42 1.2k
Daniel Sullivan United States 10 331 0.4× 230 1.1× 11 0.1× 135 0.7× 198 1.1× 20 1.1k
Uchechukwu C. Megwalu United States 21 132 0.2× 46 0.2× 51 0.3× 18 0.1× 464 2.7× 82 1.6k
Tan Arulampalam United Kingdom 17 388 0.5× 53 0.2× 65 0.3× 6 0.0× 609 3.5× 44 1.4k
Hanna M. Zafar United States 18 461 0.6× 16 0.1× 11 0.1× 112 0.6× 149 0.9× 65 876
Wen Wan United States 15 172 0.2× 96 0.4× 7 0.0× 32 0.2× 59 0.3× 55 797
John Hanrahan United Kingdom 14 111 0.1× 18 0.1× 110 0.6× 21 0.1× 181 1.0× 61 1.0k
Bethany Williams United Kingdom 16 293 0.4× 22 0.1× 5 0.0× 491 2.6× 239 1.4× 35 963
Anna P. Lietz United States 9 50 0.1× 133 0.6× 21 0.1× 16 0.1× 317 1.8× 15 641
Heather Deans United Kingdom 12 71 0.1× 25 0.1× 26 0.1× 73 0.4× 130 0.7× 21 432
Kedar Jambhekar United States 15 152 0.2× 39 0.2× 79 0.4× 12 0.1× 55 0.3× 57 724

Countries citing papers authored by Sora C. Yoon

Since Specialization
Citations

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

Fields of papers citing papers by Sora C. Yoon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sora C. Yoon. 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 Sora C. Yoon. The network helps show where Sora C. Yoon may publish in the future.

Co-authorship network of co-authors of Sora C. Yoon

This figure shows the co-authorship network connecting the top 25 collaborators of Sora C. Yoon. A scholar is included among the top collaborators of Sora C. Yoon 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 Sora C. Yoon. Sora C. Yoon 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.
Yoon, Sora C., et al.. (2025). Association between temporomandibular disorders and mental and behavioural disorders - a nationwide population-based cross-sectional study. Clinical Oral Investigations. 29(5). 234–234. 1 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.
Grimm, Lars J., Rebecca A. Shelby, Stamatia Destounis, et al.. (2024). Now or Later? Patient Satisfaction and Anxiety Among Women Undergoing Breast Biopsies Performed the Same Day as Recommended Versus a Later Day. Journal of the American College of Radiology. 21(3). 415–424. 2 indexed citations
4.
Yoon, Sora C., et al.. (2023). Racial Disparities in Breast Imaging Wait Times Before and After the Implementation of a Same-Day Biopsy Program. Journal of Breast Imaging. 5(2). 159–166. 4 indexed citations
5.
Yoon, Sora C., et al.. (2023). Impact of Interruptions During Screening Mammography on Physician Well-Being and Patient Care. Journal of the American College of Radiology. 21(6). 896–904. 2 indexed citations
6.
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
7.
Lee, Yueh Z., Connor Puett, Christina R. Inscoe, et al.. (2019). Initial Clinical Experience with Stationary Digital Breast Tomosynthesis. Academic Radiology. 26(10). 1363–1372. 6 indexed citations
8.
Campbell, James C., Sora C. Yoon, & Lars J. Grimm. (2018). Authorship and Impact of Gender-Specific Research in Major Radiology Journals. Journal of the American College of Radiology. 16(2). 240–243. 19 indexed citations
9.
Campbell, James C., et al.. (2017). Factors Influencing the Gender Breakdown of Academic Radiology Residency Programs. Journal of the American College of Radiology. 14(7). 958–962. 35 indexed citations
10.
Grimm, Lars J., et al.. (2017). Differential Motivations for Pursuing Diagnostic Radiology by Gender. Academic Radiology. 24(10). 1312–1317. 32 indexed citations
11.
Shelby, Rebecca A., et al.. (2016). Patient Anxiety Before and Immediately After Imaging-Guided Breast Biopsy Procedures: Impact of Radiologist-Patient Communication. Journal of the American College of Radiology. 13(11). e62–e71. 22 indexed citations
12.
Grimm, Lars J., Mary Scott Soo, Sora C. Yoon, et al.. (2015). Abbreviated Screening Protocol for Breast MRI. Academic Radiology. 22(9). 1157–1162. 121 indexed citations
13.
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
14.
Lee, Sang-Gun, et al.. (2014). Factors Influencing the Adoption of Enterprise Cloud Computing. 網際網路技術學刊. 15(1). 65–75. 2 indexed citations
15.
Mazurowski, Maciej A., et al.. (2014). Radiogenomic Analysis of Breast Cancer: Luminal B Molecular Subtype Is Associated with Enhancement Dynamics at MR Imaging. Radiology. 273(2). 365–372. 197 indexed citations
16.
Shelby, Rebecca A., Karen S. Johnson, Anava Wren, et al.. (2014). Predictors of Pain Experienced by Women During Percutaneous Imaging-Guided Breast Biopsies. Journal of the American College of Radiology. 11(7). 709–716. 37 indexed citations
17.
18.
Shelby, Rebecca A., et al.. (2013). Patient Anxiety Before and Immediately After Imaging-Guided Breast Biopsy Procedures: Impact of Radiologist-Patient Communication. Journal of the American College of Radiology. 10(6). 423–431. 49 indexed citations
19.
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
20.
Gollub, Marc J., et al.. (2005). Does the CT Whirl Sign Really Predict Small Bowel Volvulus?. Journal of Computer Assisted Tomography. 30(1). 25–32. 43 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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