Sunan Cui

896 total citations
18 papers, 574 citations indexed

About

Sunan Cui is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Sunan Cui has authored 18 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Radiation and 8 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Sunan Cui's work include Radiomics and Machine Learning in Medical Imaging (13 papers), Advanced Radiotherapy Techniques (9 papers) and Lung Cancer Diagnosis and Treatment (6 papers). Sunan Cui is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), Advanced Radiotherapy Techniques (9 papers) and Lung Cancer Diagnosis and Treatment (6 papers). Sunan Cui collaborates with scholars based in United States, Australia and Hong Kong. Sunan Cui's co-authors include Issam El Naqa, Randall K. Ten Haken, Yi Luo, H. Eric Tseng, Lise Wei, Jen‐Tzung Chien, Dipesh Niraula, Yi Luo, Issam M. El Naqa and Jie Fu and has published in prestigious journals such as Clinical Cancer Research, International Journal of Radiation Oncology*Biology*Physics and Medical Physics.

In The Last Decade

Sunan Cui

16 papers receiving 558 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sunan Cui United States	11	356	158	139	133	103	18	574
Siri Willems Belgium	11	342 1.0×	158 1.0×	185 1.3×	97 0.7×	107 1.0×	14	616
Saikit Lam Hong Kong	17	488 1.4×	133 0.8×	173 1.2×	198 1.5×	143 1.4×	53	749
Jianghong Xiao China	16	362 1.0×	149 0.9×	247 1.8×	145 1.1×	121 1.2×	48	689
Lise Wei United States	13	627 1.8×	176 1.1×	53 0.4×	218 1.6×	197 1.9×	24	860
John A. Onofrey United States	15	610 1.7×	104 0.7×	129 0.9×	70 0.5×	226 2.2×	69	880
Liesbeth Vandewinckele Belgium	7	398 1.1×	139 0.9×	250 1.8×	112 0.8×	129 1.3×	11	593
Mishka Gidwani United States	5	315 0.9×	143 0.9×	30 0.2×	107 0.8×	62 0.6×	7	480
Paul Desbordes France	9	285 0.8×	142 0.9×	24 0.2×	104 0.8×	71 0.7×	13	534
Seyed Masoud Rezaeijo Iran	17	406 1.1×	174 1.1×	34 0.2×	163 1.2×	110 1.1×	31	603
Oliver Díaz Spain	16	719 2.0×	538 3.4×	55 0.4×	345 2.6×	162 1.6×	72	970

Countries citing papers authored by Sunan Cui

Since Specialization

Citations

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

Fields of papers citing papers by Sunan Cui

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunan Cui

This figure shows the co-authorship network connecting the top 25 collaborators of Sunan Cui. A scholar is included among the top collaborators of Sunan Cui 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 Sunan Cui. Sunan Cui 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:

18 of 18 papers shown

Cui, Sunan, Ning Cao, Jing Zeng, et al.. (2025). Abstract P001: Discovery and validation of mTOR as an immune mediator of the FLASH effect. Clinical Cancer Research. 31(2_Supplement). P001–P001. 1 indexed citations

Wu, Yufan, Sunan Cui, Jie Fu, et al.. (2024). Chest wall pain after single-fraction thoracic stereotactic ablative Radiotherapy: Dosimetric analysis from the iSABR trial. Radiotherapy and Oncology. 196. 110317–110317.

Cui, Sunan, Cynthia Chuang, Nataliya Kovalchuk, et al.. (2024). A time- and space-saving Monte Carlo simulation method using post-collimation generative adversarial network for dose calculation of an O-ring gantry Linac. Physica Medica. 119. 103318–103318.

Saini, Jatinder, Sunan Cui, Séverine Rossomme, et al.. (2024). Commissioning a clinical proton pencil beam scanning beamline for pre-clinical ultra-high dose rate irradiations on a cyclotron-based system. Frontiers in Oncology. 14. 1460288–1460288. 1 indexed citations

Cui, Sunan, Alberto Traverso, Dipesh Niraula, et al.. (2023). Interpretable artificial intelligence in radiology and radiation oncology. British Journal of Radiology. 96(1150). 20230142–20230142. 9 indexed citations

Wei, Lise, Dipesh Niraula, Jie Fu, et al.. (2023). Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration. British Journal of Radiology. 96(1150). 20230211–20230211. 63 indexed citations

Cui, Sunan, et al.. (2022). Artificial Intelligence for Outcome Modeling in Radiotherapy. Seminars in Radiation Oncology. 32(4). 351–364. 11 indexed citations

Niraula, Dipesh, Sunan Cui, Lise Wei, et al.. (2022). Current status and future developments in predicting outcomes in radiation oncology. British Journal of Radiology. 95(1139). 20220239–20220239. 15 indexed citations

Li, Bing, Xiaoli Zheng, Jiang Zhang, et al.. (2022). Lung Subregion Partitioning by Incremental Dose Intervals Improves Omics-Based Prediction for Acute Radiation Pneumonitis in Non-Small-Cell Lung Cancer Patients. Cancers. 14(19). 4889–4889. 19 indexed citations

10.

Cui, Sunan & Guillem Pratx. (2022). 3D computational model of oxygen depletion kinetics in brain vasculature during FLASH RT and its implications for in vivo oximetry experiments. Medical Physics. 49(6). 3914–3925. 10 indexed citations

11.

Cui, Sunan, Randall K. Ten Haken, & Issam El Naqa. (2021). Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics. 110(3). 893–904. 48 indexed citations

12.

Cui, Sunan, et al.. (2020). Introduction to machine and deep learning for medical physicists. Medical Physics. 47(5). e127–e147. 85 indexed citations

13.

Luo, Yi, H. Eric Tseng, Sunan Cui, et al.. (2019). Balancing accuracy and interpretability of machine learning approaches for radiation treatment outcomes modeling. BJR|Open. 1(1). 20190021–20190021. 77 indexed citations

14.

Cui, Sunan, Yi Luo, H. Eric Tseng, Randall K. Ten Haken, & Issam El Naqa. (2019). Combining handcrafted features with latent variables in machine learning for prediction of radiation‐induced lung damage. Medical Physics. 46(5). 2497–2511. 38 indexed citations

15.

Cui, Sunan, Yi Luo, H. Eric Tseng, Randall K. Ten Haken, & Issam El Naqa. (2018). Artificial Neural Network With Composite Architectures for Prediction of Local Control in Radiotherapy. IEEE Transactions on Radiation and Plasma Medical Sciences. 3(2). 242–249. 13 indexed citations

16.

Tseng, H. Eric, Lise Wei, Sunan Cui, et al.. (2018). Machine Learning and Imaging Informatics in Oncology. Oncology. 98(6). 344–362. 46 indexed citations

17.

Cui, Sunan, Yunan Luo, S. Jolly, Randall K. Ten Haken, & Issam El Naqa. (2018). Prediction of Local Control in Non-Small Cell Lung Cancer Patients after Radiation Therapy by Composite Deep Learning Neural Networks. International Journal of Radiation Oncology*Biology*Physics. 102(3). S4–S5. 1 indexed citations

18.

Luo, Yi, et al.. (2017). Deep reinforcement learning for automated radiation adaptation in lung cancer. Medical Physics. 44(12). 6690–6705. 137 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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