Shengtao Dong

439 total citations
21 papers, 305 citations indexed

About

Shengtao Dong is a scholar working on Pulmonary and Respiratory Medicine, Surgery and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Shengtao Dong has authored 21 papers receiving a total of 305 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Pulmonary and Respiratory Medicine, 7 papers in Surgery and 7 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Shengtao Dong's work include Sarcoma Diagnosis and Treatment (12 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Bone Tumor Diagnosis and Treatments (4 papers). Shengtao Dong is often cited by papers focused on Sarcoma Diagnosis and Treatment (12 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Bone Tumor Diagnosis and Treatments (4 papers). Shengtao Dong collaborates with scholars based in China, Macao and United States. Shengtao Dong's co-authors include Wenle Li, Zhi‐Ri Tang, Chengliang Yin, Zhaohui Hu, Haosheng Wang, Wencai Liu, Wanying Li, Xintian Cai, Qiang Liu and Kai Zhang and has published in prestigious journals such as Frontiers in Immunology, BMC Cancer and European Spine Journal.

In The Last Decade

Shengtao Dong

21 papers receiving 300 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shengtao Dong China 11 117 107 56 56 55 21 305
Graziella Di Grezia Italy 11 147 1.3× 81 0.8× 73 1.3× 88 1.6× 61 1.1× 34 391
Yuexin Tong China 11 116 1.0× 138 1.3× 68 1.2× 39 0.7× 119 2.2× 34 310
I Zuber-Jerger Germany 10 208 1.8× 79 0.7× 83 1.5× 45 0.8× 57 1.0× 36 376
Dae Yoon Kim South Korea 8 84 0.7× 81 0.8× 33 0.6× 81 1.4× 29 0.5× 15 546
Stefano Scabini Italy 15 134 1.1× 87 0.8× 61 1.1× 24 0.4× 228 4.1× 48 484
Chia‐Ling Chiang Taiwan 9 142 1.2× 110 1.0× 46 0.8× 88 1.6× 48 0.9× 31 318
Clare Beadsmoore United Kingdom 12 95 0.8× 127 1.2× 15 0.3× 119 2.1× 79 1.4× 22 378
Yuewei Zhang China 13 115 1.0× 147 1.4× 112 2.0× 77 1.4× 103 1.9× 54 440
Junichi Mazaki Japan 10 115 1.0× 79 0.7× 18 0.3× 39 0.7× 194 3.5× 45 316
Rodrigo Menezes Jales Brazil 12 110 0.9× 25 0.2× 39 0.7× 44 0.8× 51 0.9× 37 398

Countries citing papers authored by Shengtao Dong

Since Specialization
Citations

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

Fields of papers citing papers by Shengtao Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shengtao Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Shengtao Dong. A scholar is included among the top collaborators of Shengtao Dong 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 Shengtao Dong. Shengtao Dong 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.
Dong, Shengtao, et al.. (2022). Analysis of Risk Factors for Adjacent Segment Degeneration after Minimally Invasive Transforaminal Interbody Fusion at Lumbosacral Spine. Computational Intelligence and Neuroscience. 2022. 1–8. 3 indexed citations
2.
Li, Wenle, Bing Wang, Zhaohui Hu, et al.. (2022). Development and Validation of a Novel Clinical Prediction Model to Predict the Risk of Lung Metastasis from Ewing Sarcoma for Medical Human-Computer Interface. Computational Intelligence and Neuroscience. 2022. 1–10. 1 indexed citations
3.
Li, Wenle, Wencai Liu, Fida Hussain Memon, et al.. (2022). An External-Validated Prediction Model to Predict Lung Metastasis among Osteosarcoma: A Multicenter Analysis Based on Machine Learning. Computational Intelligence and Neuroscience. 2022. 1–10. 24 indexed citations
4.
Liu, Wencai, Wenle Li, Shengtao Dong, et al.. (2022). Dynamic Predictive Models with Visualized Machine Learning for Assessing the Risk of Lung Metastasis in Kidney Cancer Patients. Journal of Oncology. 2022. 1–9. 5 indexed citations
5.
Li, Wenle, Wencai Liu, Zhi‐Ri Tang, et al.. (2022). A deep belief network-based clinical decision system for patients with osteosarcoma. Frontiers in Immunology. 13. 1003347–1003347. 17 indexed citations
6.
Li, Wenle, Yafeng Liu, Wencai Liu, et al.. (2022). Machine Learning-Based Prediction of Lymph Node Metastasis Among Osteosarcoma Patients. Frontiers in Oncology. 12. 797103–797103. 33 indexed citations
7.
Dong, Shengtao, et al.. (2022). Evaluation of the Predictors for Unfavorable Clinical Outcomes of Degenerative Lumbar Spondylolisthesis After Lumbar Interbody Fusion Using Machine Learning. Frontiers in Public Health. 10. 835938–835938. 10 indexed citations
8.
9.
Li, Wenle, Wencai Liu, Shengtao Dong, et al.. (2022). Development of a Machine Learning-Based Predictive Model for Lung Metastasis in Patients With Ewing Sarcoma. Frontiers in Medicine. 9. 807382–807382. 17 indexed citations
10.
Li, Wenle, Shengtao Dong, Bing Wang, et al.. (2022). The Construction and Development of a Clinical Prediction Model to Assess Lymph Node Metastases in Osteosarcoma. Frontiers in Public Health. 9. 813625–813625. 12 indexed citations
11.
Li, Wenle, Shengtao Dong, Yuewei Lin, et al.. (2022). A tool for predicting overall survival in patients with Ewing sarcoma: a multicenter retrospective study. BMC Cancer. 22(1). 914–914. 8 indexed citations
12.
Li, Wenle, Wang Gui, Shengtao Dong, et al.. (2022). Dynamic Predictive Models With Visualized Machine Learning for Assessing Chondrosarcoma Overall Survival. Frontiers in Oncology. 12. 880305–880305. 6 indexed citations
13.
Dong, Shengtao, et al.. (2022). Predictors of adverse events after percutaneous pedicle screws fixation in patients with single-segment thoracolumbar burst fractures. BMC Musculoskeletal Disorders. 23(1). 168–168. 5 indexed citations
14.
Li, Wenle, Zhaohui Hu, Shengtao Dong, et al.. (2022). A Visualized Dynamic Prediction Model for Lymphatic Metastasis in Ewing's Sarcoma for Smart Medical Services. Frontiers in Public Health. 10. 877736–877736. 3 indexed citations
15.
Li, Wenle, Wencai Liu, Zhi‐Ri Tang, et al.. (2022). A Machine Learning-Based Predictive Model for Predicting Lymph Node Metastasis in Patients With Ewing’s Sarcoma. Frontiers in Medicine. 9. 832108–832108. 21 indexed citations
16.
Li, Wenle, Bing Wang, Qiang Liu, et al.. (2022). Interpretable clinical visualization model for prediction of prognosis in osteosarcoma: a large cohort data study. Frontiers in Oncology. 12. 945362–945362. 8 indexed citations
17.
Li, Wenle, Shengtao Dong, Zhi‐Ri Tang, et al.. (2021). Risk analysis of pulmonary metastasis of chondrosarcoma by establishing and validating a new clinical prediction model: a clinical study based on SEER database. BMC Musculoskeletal Disorders. 22(1). 529–529. 26 indexed citations
18.
19.
Dong, Shengtao, et al.. (2021). Development and Validation of a Predictive Model to Evaluate the Risk of Bone Metastasis in Kidney Cancer. Frontiers in Oncology. 11. 731905–731905. 17 indexed citations
20.

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Graziella Di Grezia Breakdown of academic impact, for papers by Yuexin Tong Breakdown of academic impact, for papers by I Zuber-Jerger Breakdown of academic impact, for papers by Dae Yoon Kim Breakdown of academic impact, for papers by Stefano Scabini Breakdown of academic impact, for papers by Chia‐Ling Chiang Breakdown of academic impact, for papers by Clare Beadsmoore Breakdown of academic impact, for papers by Yuewei Zhang Breakdown of academic impact, for papers by Junichi Mazaki Breakdown of academic impact, for papers by Rodrigo Menezes Jales
Rankless by CCL
2026