Caroline Chung

9.9k total citations · 2 hit papers
216 papers, 5.1k citations indexed

About

Caroline Chung is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Genetics. According to data from OpenAlex, Caroline Chung has authored 216 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Pulmonary and Respiratory Medicine, 72 papers in Radiology, Nuclear Medicine and Imaging and 71 papers in Genetics. Recurrent topics in Caroline Chung's work include Glioma Diagnosis and Treatment (71 papers), Brain Metastases and Treatment (58 papers) and Radiomics and Machine Learning in Medical Imaging (34 papers). Caroline Chung is often cited by papers focused on Glioma Diagnosis and Treatment (71 papers), Brain Metastases and Treatment (58 papers) and Radiomics and Machine Learning in Medical Imaging (34 papers). Caroline Chung collaborates with scholars based in United States, Canada and United Kingdom. Caroline Chung's co-authors include Cynthia Ménard, Paul D. Brown, Evanthia Galanis, Volker W. Stieber, Jane H. Cerhan, Anthony L. Asher, Richard L. Deming, S. Keith Anderson, Bruce E. Pollock and Jan C. Buckner and has published in prestigious journals such as Proceedings of the National Academy of Sciences, JAMA and Journal of Clinical Oncology.

In The Last Decade

Caroline Chung

203 papers receiving 5.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Effect of Radiosurgery Alone vs Radiosurgery With Whole Brain Radiation Therapy on Cognitive Function in Patients With 1 to 3 Brain Metastases

2016 1.1k citations Caroline Chung et al. profile →
Quantitative imaging biomarkers alliance (QIBA) recommendations for improved precision of DWI and DCE‐MRI derived biomarkers in multicenter oncology trials

2018 252 citations Catherine Coolens, Caroline Chung et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Caroline Chung United States	33	2.4k	1.9k	1.4k	1.2k	771	216	5.1k
Carsten Nieder Norway	41	4.1k 1.7×	2.6k 1.4×	2.4k 1.7×	1.7k 1.4×	857 1.1×	365	7.1k
Michael Bamberg Germany	45	2.3k 1.0×	2.6k 1.4×	1.0k 0.7×	1.0k 0.8×	895 1.2×	179	6.9k
Maximilian Niyazi Germany	40	2.3k 0.9×	2.1k 1.1×	928 0.7×	2.2k 1.8×	1.1k 1.4×	270	6.2k
Rita Engenhart‐Cabillic Germany	38	2.7k 1.1×	897 0.5×	926 0.7×	835 0.7×	1.0k 1.3×	193	5.1k
Yaacov Richard Lawrence Israel	29	1.7k 0.7×	828 0.4×	702 0.5×	1.1k 0.9×	357 0.5×	135	3.7k
Brian M. Alexander United States	47	3.1k 1.3×	2.3k 1.2×	2.8k 2.0×	1.2k 0.9×	1.4k 1.8×	231	7.8k
Xiaobu Ye United States	39	1.4k 0.6×	2.3k 1.2×	2.6k 1.9×	771 0.6×	946 1.2×	151	6.8k
Raymond Miralbell Switzerland	49	4.5k 1.8×	1.2k 0.6×	981 0.7×	2.1k 1.7×	684 0.9×	216	7.7k
Arnold M. Markoe United States	37	1.6k 0.6×	566 0.3×	1.1k 0.8×	1.1k 0.9×	571 0.7×	203	4.9k
Cynthia Ménard Canada	42	4.2k 1.7×	1.2k 0.6×	1.3k 1.0×	2.3k 1.8×	592 0.8×	211	7.1k

Countries citing papers authored by Caroline Chung

Since Specialization

Citations

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

Fields of papers citing papers by Caroline Chung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Caroline Chung

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Loaiza‐Bonilla, Arturo, Nikhil G. Thaker, Caroline Chung, et al.. (2025). Driving Knowledge to Action: Building a Better Future With Artificial Intelligence–Enabled Multidisciplinary Oncology. American Society of Clinical Oncology Educational Book. 45(3). e100048–e100048. 1 indexed citations

Chung, Caroline, et al.. (2025). Paving a Path to Clinical Impact with Radiomics: Enabling Reproducibility and Reach. Cancer Research. 85(13). 2353–2355.

Leary, Owen P., Mattia D. Pizzagalli, Steven A. Toms, et al.. (2024). Tumor-Associated Tractography Derived from High-Angular-Resolution Q-Space MRI May Predict Patterns of Cellular Invasion in Glioblastoma. Cancers. 16(21). 3669–3669.

Gule-Monroe, Maria, James P. Long, Vinodh A. Kumar, et al.. (2024). Diagnostic Confidence of Contrast-Enhanced T1-Weighted MRI for the Detection of Brain Metastases: 3D FSE versus 3D GRE–Based Sequences. American Journal of Neuroradiology. 46(6). 1231–1237.

Elliott, Andrew M., et al.. (2023). Development and benchmarking diffusion magnetic resonance imaging analysis for integration into radiation treatment planning. Medical Physics. 51(3). 2108–2118. 1 indexed citations

Li, Winnie, David Shultz, Normand Laperrière, et al.. (2023). Assessment of intra-fraction motion during frameless image guided Gamma Knife stereotactic radiosurgery. Physics and Imaging in Radiation Oncology. 25. 100415–100415.

Hoebel, Katharina, Christopher P. Bridge, Sara Ahmed, et al.. (2023). Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation. Radiology Artificial Intelligence. 6(1). e220231–e220231. 4 indexed citations

Wu, Chengyue, Guillermo Lorenzo, David A. Hormuth, et al.. (2022). Integrating mechanism-based modeling with biomedical imaging to build practical digital twins for clinical oncology. PubMed. 3(2). 21304–21304. 68 indexed citations

Chung, Caroline, et al.. (2022). Patient Outcomes in Laparoscopic Appendectomy With Acute Surgical Care Model Compared to Traditional Call. Journal of Surgical Research. 281. 282–288. 1 indexed citations

10.

Butner, Joseph D., Prashant Dogra, Caroline Chung, et al.. (2022). Mathematical modeling of cancer immunotherapy for personalized clinical translation. Nature Computational Science. 2(12). 785–796. 32 indexed citations

11.

Butner, Joseph D., et al.. (2022). Protocol for mathematical prediction of patient response and survival to immune checkpoint inhibitor immunotherapy. STAR Protocols. 3(4). 101886–101886. 1 indexed citations

12.

Dogra, Prashant, Javier Ruiz-Ramírez, Joseph D. Butner, et al.. (2022). Translational Modeling Identifies Synergy between Nanoparticle-Delivered miRNA-22 and Standard-of-Care Drugs in Triple-Negative Breast Cancer. Pharmaceutical Research. 39(3). 511–528. 15 indexed citations

13.

Chung, Caroline, et al.. (2022). PocketNet: A Smaller Neural Network for Medical Image Analysis. IEEE Transactions on Medical Imaging. 42(4). 1172–1184. 20 indexed citations

14.

Butner, Joseph D., Zhihui Wang, Dalia Elganainy, et al.. (2021). A mathematical model for the quantification of a patient’s sensitivity to checkpoint inhibitors and long-term tumour burden. Nature Biomedical Engineering. 5(4). 297–308. 28 indexed citations

15.

Hormuth, David A., Angela M. Jarrett, Guillermo Lorenzo, et al.. (2021). Math, magnets, and medicine: enabling personalized oncology. Expert Review of Precision Medicine and Drug Development. 6(2). 79–81. 20 indexed citations

16.

Majd, Nazanin, Gregory N. Fuller, Jason T. Huse, et al.. (2019). RBM10 truncation in astroblastoma in a patient with history of mandibular ameloblastoma: A case report. Cancer Genetics. 231-232. 41–45. 4 indexed citations

17.

McTyre, E., D.N. Ayala-Peacock, Joseph N. Contessa, et al.. (2016). Multi-Institutional Competing Risks Analysis Predicting Distant Brain Failure and Salvage Patterns After Upfront Radiosurgery Without Whole-Brain Radiation Therapy for Brain Metastasis. International Journal of Radiation Oncology*Biology*Physics. 96(2). S180–S181. 1 indexed citations

18.

Coolens, Catherine, Brandon Driscoll, Warren D. Foltz, David A. Jaffray, & Caroline Chung. (2015). Early Detection of Tumor Response Using Volumetric DCE-CT and DCE-MRI in Metastatic Brain Patients Treated With Radiosurgery. International Journal of Radiation Oncology*Biology*Physics. 93(3). S7–S7. 3 indexed citations

19.

Hussein, Heba, Caroline Chung, Hadas Moshonov, et al.. (2015). Evaluation of Apparent Diffusion Coefficient to Predict Grade, Microinvasion, and Invasion in Ductal Carcinoma In Situ of the Breast. Academic Radiology. 22(12). 1483–1488. 16 indexed citations

20.

Chung, Caroline, Kenji Ohwaki, Jonathan E. Schneeweis, et al.. (2008). A Fluorescence-Based Thiol Quantification Assay for Ultra-High-Throughput Screening for Inhibitors of Coenzyme A Production. Assay and Drug Development Technologies. 6(3). 361–374. 37 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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