Annan Dong

441 total citations
23 papers, 288 citations indexed

About

Annan Dong is a scholar working on Surgery, Otorhinolaryngology and Oncology. According to data from OpenAlex, Annan Dong has authored 23 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Surgery, 13 papers in Otorhinolaryngology and 6 papers in Oncology. Recurrent topics in Annan Dong's work include Head and Neck Cancer Studies (13 papers), Head and Neck Surgical Oncology (9 papers) and Salivary Gland Tumors Diagnosis and Treatment (7 papers). Annan Dong is often cited by papers focused on Head and Neck Cancer Studies (13 papers), Head and Neck Surgical Oncology (9 papers) and Salivary Gland Tumors Diagnosis and Treatment (7 papers). Annan Dong collaborates with scholars based in China, United States and United Kingdom. Annan Dong's co-authors include Haojiang Li, Chunyan Cui, Lizhi Liu, Lujun Shen, Jian Zhou, Sheng Li, Lizhi Liu, Peihong Wu, Ming‐Yuan Chen and Shaobo Liang and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Vehicular Technology and American Journal of Roentgenology.

In The Last Decade

Annan Dong

23 papers receiving 286 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Annan Dong China 12 183 119 99 87 67 23 288
Andriana Michaelidou United Kingdom 9 96 0.5× 110 0.9× 208 2.1× 85 1.0× 142 2.1× 17 321
Jing Ou China 9 50 0.3× 115 1.0× 123 1.2× 40 0.5× 83 1.2× 27 239
Guoping Shan China 10 102 0.6× 69 0.6× 116 1.2× 43 0.5× 123 1.8× 34 305
Karin Söderkvist Sweden 9 79 0.4× 106 0.9× 84 0.8× 65 0.7× 114 1.7× 32 279
Michael Benedict A. Mejia Philippines 8 113 0.6× 73 0.6× 95 1.0× 68 0.8× 98 1.5× 28 285
Yishu Deng China 9 65 0.4× 33 0.3× 82 0.8× 22 0.3× 62 0.9× 25 225
Benjamin Rosen United States 11 70 0.4× 36 0.3× 220 2.2× 26 0.3× 138 2.1× 32 344
Phillip Beron United States 5 204 1.1× 135 1.1× 39 0.4× 87 1.0× 104 1.6× 10 298

Countries citing papers authored by Annan Dong

Since Specialization
Citations

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

Fields of papers citing papers by Annan Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Annan Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Annan Dong. A scholar is included among the top collaborators of Annan 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 Annan Dong. Annan 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, Annan, et al.. (2023). Matted Lymph Nodes on MRI in Nasopharyngeal Carcinoma: Prognostic Factor and Potential Indication for Induction Chemotherapy Benefits. Journal of Magnetic Resonance Imaging. 59(6). 1976–1990. 1 indexed citations
2.
Zhao, Qin, Annan Dong, Guangying Ruan, et al.. (2022). MRI‐Based Metastatic Nodal Number and Associated Nomogram Improve Stratification of Nasopharyngeal Carcinoma Patients: Potential Indications for Individual Induction Chemotherapy. Journal of Magnetic Resonance Imaging. 57(6). 1790–1802. 9 indexed citations
3.
Xie, Fei, Qin Zhao, Shuqi Li, et al.. (2022). Establishment and validation of novel MRI radiomic feature-based prognostic models to predict progression-free survival in locally advanced rectal cancer. Frontiers in Oncology. 12. 901287–901287. 5 indexed citations
4.
Cao, Di, et al.. (2022). Systematic construction and external validation of an immune‐related prognostic model for nasopharyngeal carcinoma. Head & Neck. 44(5). 1086–1098. 2 indexed citations
5.
Wu, Shuangshuang, Haojiang Li, Annan Dong, et al.. (2021). Differences in Radiomics Signatures Between Patients with Early and Advanced T‐Stage Nasopharyngeal Carcinoma Facilitate Prognostication. Journal of Magnetic Resonance Imaging. 54(3). 854–865. 14 indexed citations
6.
Dong, Jun, et al.. (2021). Follicular Dendritic Cell Sarcomas: CT and MRI Findings in 20 Patients. American Journal of Roentgenology. 216(3). 835–843. 9 indexed citations
8.
Haimovich, Alexander M., et al.. (2020). Blind Source Separation with L1 Regularized Sparse Autoencoder. 1–5. 2 indexed citations
9.
Cui, Chunyan, et al.. (2020). Grading and prognosis of weight loss before and after treatment with optimal cutoff values in nasopharyngeal carcinoma. Nutrition. 78. 110943–110943. 5 indexed citations
10.
Li, Haojiang, Fei Xie, Guangying Ruan, et al.. (2020). Prognostic Value of Nodal Matting on MRI in Nasopharyngeal Carcinoma Patients. Journal of Magnetic Resonance Imaging. 53(1). 152–164. 16 indexed citations
11.
Cui, Chunyan, Shunxin Wang, Jian Zhou, et al.. (2020). Machine Learning Analysis of Image Data Based on Detailed MR Image Reports for Nasopharyngeal Carcinoma Prognosis. BioMed Research International. 2020(1). 8068913–8068913. 19 indexed citations
12.
Tang, Xiaofeng, Jiang Wu, Haojiang Li, et al.. (2020). Predicting poor response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer: Model constructed using pre-treatment MRI features of structured report template. Radiotherapy and Oncology. 148. 97–106. 14 indexed citations
13.
Cui, Chunyan, Haojiang Li, Annan Dong, et al.. (2020). Staging of T2 and T3 nasopharyngeal carcinoma: Proposed modifications for improving the current AJCC staging system. Cancer Medicine. 9(20). 7572–7579. 12 indexed citations
14.
Dong, Annan, et al.. (2020). Sparse Recovery of Intermittent Frequency Hopping Signals Aided by DOA. 50. 1–6. 2 indexed citations
15.
Liu, Yifei, Annan Dong, Fei Ai, et al.. (2019). Nodal grouping in nasopharyngeal carcinoma: prognostic significance, N classification, and a marker for the identification of candidates for induction chemotherapy. European Radiology. 30(4). 2115–2124. 30 indexed citations
16.
Dong, Annan, et al.. (2019). Blind Sparse Estimation of Intermittent Sources Over Unknown Fading Channels. IEEE Transactions on Vehicular Technology. 68(10). 9861–9871. 4 indexed citations
17.
Dong, Jun, Liang Zhang, Wang Li, et al.. (2015). 1.0 T open-configuration magnetic resonance-guided microwave ablation of pig livers in real time. Scientific Reports. 5(1). 13551–13551. 13 indexed citations
18.
Li, Wang, Qi Zeng, Sheng Li, et al.. (2015). CT-Guided Percutaneous Step-by-Step Radiofrequency Ablation for the Treatment of Carcinoma in the Caudate Lobe. Medicine. 94(39). e1594–e1594. 13 indexed citations
19.
Shen, Lujun, Jun Dong, Sheng Li, et al.. (2015). M1 Stage Subdivision and Treatment Outcome of Patients With Bone-Only Metastasis of Nasopharyngeal Carcinoma. The Oncologist. 20(3). 291–298. 44 indexed citations
20.
Dong, Jun, Wang Li, Annan Dong, et al.. (2014). Gene therapy for unresectable hepatocellular carcinoma using recombinant human adenovirus type 5. Medical Oncology. 31(8). 95–95. 18 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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