Congxin Dai

1.7k total citations
59 papers, 1.1k citations indexed

About

Congxin Dai is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics and Surgery. According to data from OpenAlex, Congxin Dai has authored 59 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Endocrinology, Diabetes and Metabolism, 28 papers in Genetics and 20 papers in Surgery. Recurrent topics in Congxin Dai's work include Pituitary Gland Disorders and Treatments (36 papers), Glioma Diagnosis and Treatment (28 papers) and Adrenal and Paraganglionic Tumors (17 papers). Congxin Dai is often cited by papers focused on Pituitary Gland Disorders and Treatments (36 papers), Glioma Diagnosis and Treatment (28 papers) and Adrenal and Paraganglionic Tumors (17 papers). Congxin Dai collaborates with scholars based in China, United States and Canada. Congxin Dai's co-authors include Renzhi Wang, Yong Yao, Bowen Sun, Ming Feng, Wenbin Ma, Jun Kang, Xiaohai Liu, Xinjie Bao, Yaning Wang and Ziren Kong and has published in prestigious journals such as Nature Genetics, The Journal of Experimental Medicine and Endocrinology.

In The Last Decade

Congxin Dai

58 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Congxin Dai China 21 364 340 306 215 187 59 1.1k
Hidehisa Horiguchi Japan 18 212 0.6× 157 0.5× 238 0.8× 305 1.4× 144 0.8× 41 1.0k
Josefin Ahnström United Kingdom 22 229 0.6× 183 0.5× 804 2.6× 433 2.0× 166 0.9× 53 1.8k
Sang Hoon Shin South Korea 17 116 0.3× 388 1.1× 321 1.0× 175 0.8× 106 0.6× 47 1.1k
Ki Cheol Park South Korea 23 261 0.7× 65 0.2× 673 2.2× 195 0.9× 184 1.0× 49 1.4k
Hidekazu Ota Japan 18 74 0.2× 119 0.3× 277 0.9× 243 1.1× 139 0.7× 74 1.3k
Hyun Jeong Jeong South Korea 16 51 0.1× 316 0.9× 502 1.6× 407 1.9× 194 1.0× 28 1.3k
Tineke Kok Netherlands 8 133 0.4× 211 0.6× 550 1.8× 760 3.5× 115 0.6× 11 1.5k
Frédérique Deshayes France 19 165 0.5× 104 0.3× 545 1.8× 56 0.3× 143 0.8× 31 1.2k
Mustafa Aziz Hatiboğlu Türkiye 21 68 0.2× 645 1.9× 193 0.6× 259 1.2× 88 0.5× 71 1.4k
Christine Hsu United States 16 99 0.3× 85 0.3× 410 1.3× 457 2.1× 142 0.8× 38 2.2k

Countries citing papers authored by Congxin Dai

Since Specialization
Citations

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

Fields of papers citing papers by Congxin Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Congxin Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Congxin Dai. A scholar is included among the top collaborators of Congxin Dai 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 Congxin Dai. Congxin Dai 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.
Wang, He, Xiao-Hai Liu, Congxin Dai, et al.. (2024). Predicting delayed remission in Cushing’s disease using radiomics models: a multi-center study. Frontiers in Oncology. 13. 1218897–1218897. 4 indexed citations
2.
Li, Yong, Hao Dong, Shangfeng Zhao, et al.. (2023). Craniofacial Fibrous Dysplasia in Fronto-Orbital Region: A Single-Center Retrospective Study of 38 Cases. World Neurosurgery. 181. e1130–e1137. 2 indexed citations
3.
Liu, Xiaohai, Congxin Dai, Xinjie Bao, et al.. (2022). The Clinical and Pathological Characteristics of Refractory Pituitary Adenomas: A Single Center Experience. Frontiers in Oncology. 12. 846614–846614. 9 indexed citations
4.
Dai, Congxin, Ming Feng, Lin Lü, et al.. (2022). Transsphenoidal Surgery of Corticotroph Adenomas With Cavernous Sinus Invasion: Results in a Series of 86 Consecutive Patients. Frontiers in Oncology. 12. 810234–810234. 1 indexed citations
5.
Han, Yan, Yadong Wang, Yuekun Wang, et al.. (2021). A Bayesian network meta-analysis regarding the comparative efficacy of therapeutics for ALK-positive, brain metastatic non-small cell lung cancer. Pharmacological Research. 174. 105931–105931. 9 indexed citations
6.
Dai, Congxin, Jun Kang, Xiaohai Liu, et al.. (2021). How to Classify and Define Pituitary Tumors: Recent Advances and Current Controversies. Frontiers in Endocrinology. 12. 604644–604644. 20 indexed citations
7.
Lei, Chuxiang, Wenlin Chen, Yuekun Wang, et al.. (2021). Prognostic Prediction Model for Glioblastoma: A Metabolic Gene Signature and Independent External Validation. Journal of Cancer. 12(13). 3796–3808. 15 indexed citations
8.
Zhou, Xin, Seula Shin, Chenxi He, et al.. (2021). Qki regulates myelinogenesis through Srebp2-dependent cholesterol biosynthesis. eLife. 10. 21 indexed citations
9.
Liu, Xiao-Hai, Ming Feng, Congxin Dai, et al.. (2020). Internal carotid artery injury in the endoscopic transsphenoidal surgery for pituitary adenoma: an uncommon case and literature review. Gland Surgery. 9(4). 1036–1041. 5 indexed citations
10.
Dai, Congxin, Siyu Liang, Xiao-Hai Liu, et al.. (2020). Outcomes of Transsphenoidal Surgery in Cushing Disease Patients with Negative Pituitary Magnetic Resonance Imaging Findings: A Single-Center Experience. Endocrine Practice. 26(11). 1320–1330. 5 indexed citations
11.
Wang, Yaning, Binghao Zhao, Wanqi Chen, et al.. (2020). Pretreatment Geriatric Assessments of Elderly Patients with Glioma: Development and Implications. Aging and Disease. 11(2). 448–448. 16 indexed citations
12.
Dai, Congxin, Siyu Liang, Bowen Sun, & Jun Kang. (2020). The Progress of Immunotherapy in Refractory Pituitary Adenomas and Pituitary Carcinomas. Frontiers in Endocrinology. 11. 608422–608422. 41 indexed citations
13.
Sun, Xiaolin, Lin Lü, Ming Feng, et al.. (2020). Cushing Syndrome Caused by Ectopic Adrenocorticotropic Hormone–Secreting Pituitary Adenomas: Case Report and Literature Review. World Neurosurgery. 142. 75–86. 7 indexed citations
14.
Kong, Ziren, Yusong Lin, Longfei Li, et al.. (2019). 18F-FDG-PET-based Radiomics signature predicts MGMT promoter methylation status in primary diffuse glioma. Cancer Imaging. 19(1). 58–58. 39 indexed citations
15.
Liu, Xiao-Hai, Ming Feng, Congxin Dai, et al.. (2019). Expression of EGFR in Pituitary Corticotroph Adenomas and Its Relationship With Tumor Behavior. Frontiers in Endocrinology. 10. 785–785. 17 indexed citations
17.
Shingu, Takashi, Allen L. Ho, Liang Yuan, et al.. (2016). Qki deficiency maintains stemness of glioma stem cells in suboptimal environment by downregulating endolysosomal degradation. Nature Genetics. 49(1). 75–86. 74 indexed citations
18.
Kong, Xiangyi, Yu Wang, Congxin Dai, Wenbin Ma, & Renzhi Wang. (2016). Is CD147 a New Biomarker Reflecting Histological Malignancy of Gliomas?. Molecular Neurobiology. 54(2). 1568–1576. 5 indexed citations
19.
Lv, Shunzeng, Bowen Sun, Xiao Yan Zhong, et al.. (2014). The Clinical Implications of Chemokine Receptor CXCR4 in Grade and Prognosis of Glioma Patients: A Meta-Analysis. Molecular Neurobiology. 52(1). 555–561. 12 indexed citations
20.
Yang, Yakun, Miaomiao Sheng, Fengming Huang, et al.. (2013). Downregulation of Insulin-like growth factor binding protein 6 is associated with ACTH-secreting pituitary adenoma growth. Pituitary. 17(6). 505–513. 9 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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