Connie Kim

612 total citations
13 papers, 460 citations indexed

About

Connie Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Pathology and Forensic Medicine. According to data from OpenAlex, Connie Kim has authored 13 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Artificial Intelligence and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Connie Kim's work include AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and MRI in cancer diagnosis (4 papers). Connie Kim is often cited by papers focused on AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and MRI in cancer diagnosis (4 papers). Connie Kim collaborates with scholars based in United States, China and South Korea. Connie Kim's co-authors include Sora C. Yoon, Mary Scott Soo, Lars J. Grimm, Karen S. Johnson, Sujata V. Ghate, Sujata V. Ghate, Maciej A. Mazurowski, R. Brooke Jeffrey, Stuart E. Mirvis and Philip W. Ralls and has published in prestigious journals such as American Journal of Roentgenology, Medical Physics and European Journal of Radiology.

In The Last Decade

Connie Kim

13 papers receiving 455 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Connie Kim United States	9	242	109	68	59	55	13	460
Xiaomeng Lei United States	12	297 1.2×	58 0.5×	199 2.9×	58 1.0×	6 0.1×	44	450
Steven Liu United States	10	69 0.3×	111 1.0×	20 0.3×	6 0.1×	14 0.3×	44	333
Cláudia Sà dos Reis Switzerland	12	226 0.9×	27 0.2×	109 1.6×	69 1.2×	8 0.1×	47	394
Sara Golla United States	8	138 0.6×	23 0.2×	121 1.8×	90 1.5×	14 0.3×	9	308
Bojan Kovacina Canada	9	121 0.5×	67 0.6×	126 1.9×	14 0.2×	7 0.1×	14	313
John P. Garcia United States	10	23 0.1×	76 0.7×	19 0.3×	17 0.3×	11 0.2×	44	314
Aditya Borakati United Kingdom	9	89 0.4×	38 0.3×	17 0.3×	31 0.5×	4 0.1×	15	262
Nicasio Pérez‐Castellano Spain	19	176 0.7×	293 2.7×	99 1.5×	3 0.1×	22 0.4×	79	1.5k
Amar Patel United States	12	117 0.5×	39 0.4×	27 0.4×	29 0.5×	14 0.3×	26	333
Join Y. Luh United States	10	52 0.2×	90 0.8×	52 0.8×	14 0.2×	14 0.3×	29	318

Countries citing papers authored by Connie Kim

Since Specialization

Citations

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

Fields of papers citing papers by Connie Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Connie Kim

This figure shows the co-authorship network connecting the top 25 collaborators of Connie Kim. A scholar is included among the top collaborators of Connie Kim 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 Connie Kim. Connie Kim is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

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

Grimm, Lars J., Benjamin Neely, Rui Hou, et al.. (2020). Mixed-Methods Study to Predict Upstaging of DCIS to Invasive Disease on Mammography. American Journal of Roentgenology. 216(4). 903–911. 7 indexed citations

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

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

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

Shelby, Rebecca A., Anava Wren, Sarah A. Kelleher, et al.. (2016). Positive and negative mood following imaging-guided core needle breast biopsy and receipt of biopsy results. Psychology Health & Medicine. 22(10). 1149–1162. 4 indexed citations

Soo, Mary Scott, Anava Wren, Yvonne M. Mowery, et al.. (2016). Imaging-Guided Core-Needle Breast Biopsy: Impact of Meditation and Music Interventions on Patient Anxiety, Pain, and Fatigue. Journal of the American College of Radiology. 13(5). 526–534. 87 indexed citations

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

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

10.

Grimm, Lars J., Sujata V. Ghate, Sora C. Yoon, et al.. (2014). Predicting error in detecting mammographic masses among radiology trainees using statistical models based on BI‐RADS features. Medical Physics. 41(3). 9 indexed citations

11.

Samei, Ehsan, Joseph Y. Lo, Jay A. Baker, et al.. (2011). Comparative performance of multiview stereoscopic and mammographic display modalities for breast lesion detection. Medical Physics. 38(4). 1972–1980. 17 indexed citations

12.

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

13.

Jeffrey, R. Brooke, Stuart E. Mirvis, Michael P. Federle, et al.. (2002). Using Contrast-Enhanced Helical CT to Visualize Arterial Extravasation After Blunt Abdominal Trauma. American Journal of Roentgenology. 178(1). 17–20. 103 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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