Jie Shan

623 total citations
19 papers, 523 citations indexed

About

Jie Shan is a scholar working on Pulmonary and Respiratory Medicine, Radiation and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Jie Shan has authored 19 papers receiving a total of 523 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Pulmonary and Respiratory Medicine, 13 papers in Radiation and 6 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Jie Shan's work include Radiation Therapy and Dosimetry (15 papers), Advanced Radiotherapy Techniques (12 papers) and Medical Imaging Techniques and Applications (4 papers). Jie Shan is often cited by papers focused on Radiation Therapy and Dosimetry (15 papers), Advanced Radiotherapy Techniques (12 papers) and Medical Imaging Techniques and Applications (4 papers). Jie Shan collaborates with scholars based in United States, China and Belgium. Jie Shan's co-authors include Wei Liu, Martin Bues, Steven E. Schild, William W. Wong, Xiaoning Ding, Yu An, Samir H. Patel, M. Fatyga, Terence T. Sio and Chenbin Liu and has published in prestigious journals such as Scientific Reports, International Journal of Radiation Oncology*Biology*Physics and Medical Physics.

In The Last Decade

Jie Shan

18 papers receiving 523 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jie Shan United States 15 442 420 178 48 40 19 523
M. Fatyga United States 18 555 1.3× 625 1.5× 360 2.0× 41 0.9× 111 2.8× 50 764
Junan Zhang United States 13 318 0.7× 361 0.9× 366 2.1× 32 0.7× 120 3.0× 31 574
Sina Mossahebi United States 11 280 0.6× 270 0.6× 143 0.8× 23 0.5× 44 1.1× 53 401
Robert Kaderka United States 14 351 0.8× 426 1.0× 256 1.4× 62 1.3× 58 1.4× 30 538
Hideharu Miura Japan 11 227 0.5× 305 0.7× 209 1.2× 14 0.3× 69 1.7× 60 388
Vanessa Panettieri Australia 14 381 0.9× 529 1.3× 328 1.8× 18 0.4× 98 2.5× 46 598
A. Roggio Italy 10 225 0.5× 362 0.9× 248 1.4× 29 0.6× 82 2.0× 20 416
Arthur Lalonde Canada 17 426 1.0× 421 1.0× 386 2.2× 28 0.6× 332 8.3× 34 659
Anees Dhabaan United States 14 485 1.1× 578 1.4× 430 2.4× 16 0.3× 169 4.2× 41 812
Olivier Gayou United States 13 249 0.6× 325 0.8× 279 1.6× 26 0.5× 160 4.0× 29 536

Countries citing papers authored by Jie Shan

Since Specialization
Citations

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

Fields of papers citing papers by Jie Shan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jie Shan

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

All Works

19 of 19 papers shown
1.
Shan, Jie, et al.. (2024). Machine Learning Differentiates Between Benign and Malignant Parotid Tumors With Contrast-Enhanced Ultrasound Features. Journal of Oral and Maxillofacial Surgery. 83(2). 208–221.
2.
Holmes, Jason, Jiajian Shen, Jie Shan, et al.. (2022). Technical note: Evaluation and second check of a commercial Monte Carlo dose engine for small‐field apertures in pencil beam scanning proton therapy. Medical Physics. 49(5). 3497–3506. 14 indexed citations
3.
Shan, Jie, Samir H. Patel, William W. Wong, et al.. (2022). Virtual particle Monte Carlo: A new concept to avoid simulating secondary particles in proton therapy dose calculation. Medical Physics. 49(10). 6666–6683. 14 indexed citations
4.
Shan, Jie, Jonathan B. Ashman, William G. Rule, et al.. (2021). Technical Note: 4D robust optimization in small spot intensity‐modulated proton therapy (IMPT) for distal esophageal carcinoma. Medical Physics. 48(8). 4636–4647. 25 indexed citations
5.
Shan, Jie, William W. Wong, Steven E. Schild, et al.. (2021). Per‐voxel constraints to minimize hot spots in linear energy transfer‐guided robust optimization for base of skull head and neck cancer patients in IMPT. Medical Physics. 49(1). 632–647. 21 indexed citations
6.
Shan, Jie, et al.. (2021). A meta-analysis of active smoking and risk of meningioma. Tobacco Induced Diseases. 19(May). 1–8. 2 indexed citations
7.
Shan, Jie, Rui Jiang, Yi Zhong, et al.. (2020). Machine Learning Predicts Lymph Node Metastasis in Early-Stage Oral Tongue Squamous Cell Carcinoma. Journal of Oral and Maxillofacial Surgery. 78(12). 2208–2218. 37 indexed citations
8.
Deng, Wei, Kevin Souris, Sheng Huang, et al.. (2020). Technical Note: Integrating an open source Monte Carlo code “MCsquare” for clinical use in intensity‐modulated proton therapy. Medical Physics. 47(6). 2558–2574. 45 indexed citations
9.
Zhang, Hengguo, Jie Shan, Ping Zhang, Xin Chen, & Hongbing Jiang. (2020). Trabeculae microstructure parameters serve as effective predictors for marginal bone loss of dental implant in the mandible. Scientific Reports. 10(1). 18437–18437. 21 indexed citations
10.
Liu, Chenbin, Samir H. Patel, Jie Shan, et al.. (2020). Robust Optimization for Intensity Modulated Proton Therapy to Redistribute High Linear Energy Transfer from Nearby Critical Organs to Tumors in Head and Neck Cancer. International Journal of Radiation Oncology*Biology*Physics. 107(1). 181–193. 53 indexed citations
11.
12.
Liu, Chenbin, R.S. Bhangoo, Terence T. Sio, et al.. (2019). Dosimetric comparison of distal esophageal carcinoma plans for patients treated with small‐spot intensity‐modulated proton versus volumetric‐modulated arc therapies. Journal of Applied Clinical Medical Physics. 20(7). 15–27. 44 indexed citations
13.
Shen, Jiajian, Jie Shan, Martin Bues, et al.. (2019). Clinical Validation of a Ray-Casting Analytical Dose Engine for Spot Scanning Proton Delivery Systems. Technology in Cancer Research & Treatment. 18. 1078154830–1078154830. 20 indexed citations
14.
15.
Shan, Jie, Terence T. Sio, Chenbin Liu, et al.. (2018). A novel and individualized robust optimization method using normalized dose interval volume constraints (NDIVC) for intensity‐modulated proton radiotherapy. Medical Physics. 46(1). 382–393. 21 indexed citations
16.
Shan, Jie, Wei Liu, Martin Bues, et al.. (2018). Automation of routine elements for spot‐scanning proton patient‐specific quality assurance. Medical Physics. 46(1). 5–14. 14 indexed citations
17.
Shan, Jie, Yu An, Martin Bues, Steven E. Schild, & Wei Liu. (2017). Robust optimization in IMPT using quadratic objective functions to account for the minimum MU constraint. Medical Physics. 45(1). 460–469. 51 indexed citations
18.
Zhang, Pengfei, Neng Fan, Jie Shan, et al.. (2017). Mixed integer programming with dose‐volume constraints in intensity‐modulated proton therapy. Journal of Applied Clinical Medical Physics. 18(5). 29–35. 11 indexed citations
19.
An, Yu, Jie Shan, Samir H. Patel, et al.. (2017). Robust intensity‐modulated proton therapy to reduce high linear energy transfer in organs at risk. Medical Physics. 44(12). 6138–6147. 69 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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