Chaoran Yu

1.3k total citations
47 papers, 862 citations indexed

About

Chaoran Yu is a scholar working on Oncology, Pulmonary and Respiratory Medicine and Pathology and Forensic Medicine. According to data from OpenAlex, Chaoran Yu has authored 47 papers receiving a total of 862 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Oncology, 17 papers in Pulmonary and Respiratory Medicine and 12 papers in Pathology and Forensic Medicine. Recurrent topics in Chaoran Yu's work include Gastric Cancer Management and Outcomes (13 papers), Cancer Mechanisms and Therapy (8 papers) and Metastasis and carcinoma case studies (5 papers). Chaoran Yu is often cited by papers focused on Gastric Cancer Management and Outcomes (13 papers), Cancer Mechanisms and Therapy (8 papers) and Metastasis and carcinoma case studies (5 papers). Chaoran Yu collaborates with scholars based in China, Austria and United States. Chaoran Yu's co-authors include Yujie Zhang, Yujie Zhang, Yujie Zhang, Jing Ping Sun, Qiang Wang, Yi Sun, Minhua Zheng, Daxing Xie, Jianping Gong and Junbo Hu and has published in prestigious journals such as The Journal of Experimental Medicine, PLoS ONE and Scientific Reports.

In The Last Decade

Chaoran Yu

43 papers receiving 840 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chaoran Yu China 19 318 281 279 203 147 47 862
Kohei Nakamura Japan 18 251 0.8× 264 0.9× 413 1.5× 196 1.0× 200 1.4× 113 1.1k
Hejun Zhang China 19 211 0.7× 275 1.0× 247 0.9× 256 1.3× 235 1.6× 60 858
Manabu Takamatsu Japan 17 350 1.1× 192 0.7× 313 1.1× 240 1.2× 51 0.3× 83 938
Zhidong Gao China 17 370 1.2× 310 1.1× 324 1.2× 382 1.9× 248 1.7× 87 1.0k
Fuxing Zhao China 14 347 1.1× 251 0.9× 542 1.9× 103 0.5× 151 1.0× 56 948
James E. Boers Netherlands 17 592 1.9× 264 0.9× 338 1.2× 249 1.2× 127 0.9× 30 1.1k
Xiaolong Wu China 14 156 0.5× 317 1.1× 241 0.9× 102 0.5× 231 1.6× 70 723
Tokushige Kobayashi Japan 8 366 1.2× 113 0.4× 512 1.8× 208 1.0× 54 0.4× 9 878
Maobin Meng China 19 239 0.8× 231 0.8× 232 0.8× 141 0.7× 151 1.0× 46 778
Neil Sharma United Kingdom 17 212 0.7× 192 0.7× 239 0.9× 243 1.2× 200 1.4× 69 894

Countries citing papers authored by Chaoran Yu

Since Specialization
Citations

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

Fields of papers citing papers by Chaoran Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chaoran Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Chaoran Yu. A scholar is included among the top collaborators of Chaoran Yu 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 Chaoran Yu. Chaoran Yu 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.
2.
Zhou, Zhiyuan, Chaoran Yu, Danhua Yao, et al.. (2025). Machine learning-based text mining for cutaneous myiasis and potential value of an accidental maggot therapy for complicated skin and soft tissue infection with sepsis. Frontiers in Cellular and Infection Microbiology. 15. 1568563–1568563.
3.
Wang, Baohong, Yujie Wang, Danhua Yao, et al.. (2024). Impact of enhanced recovery after surgery (ERAS) on surgical site infection and postoperative recovery outcomes: a retrospective study of 1276 cases. Scientific Reports. 14(1). 24055–24055. 1 indexed citations
4.
Zhou, Zhiyuan, et al.. (2024). Landscape of surgery in Crohn’s disease across twenty years: insights from machine learning. Translational Gastroenterology and Hepatology. 9. 64–64.
5.
Yu, Chaoran, Zhiyuan Zhou, Bin Liu, et al.. (2023). Investigation of trends in gut microbiome associated with colorectal cancer using machine learning. Frontiers in Oncology. 13. 1077922–1077922. 3 indexed citations
6.
Yu, Chaoran, et al.. (2021). Role of rehabilitation amidst the COVID-19 pandemic: a review. Journal of Translational Medicine. 19(1). 376–376. 9 indexed citations
7.
Pan, Ruijun, Hiju Hong, Jing Ping Sun, et al.. (2021). Detection and Clinical Value of Circulating Tumor Cells as an Assisted Prognostic Marker in Colorectal Cancer Patients. Cancer Management and Research. Volume 13. 4567–4578. 27 indexed citations
8.
Cai, Zhenghao, Haiqin Song, Abe Fingerhut, et al.. (2021). A greater lymph node yield is required during pathological examination in microsatellite instability-high gastric cancer. BMC Cancer. 21(1). 319–319. 6 indexed citations
9.
Wang, Qiang & Chaoran Yu. (2020). Identification of biomarkers associated with extracellular vesicles based on an integrative pan-cancer bioinformatics analysis. Medical Oncology. 37(9). 79–79. 6 indexed citations
10.
Wang, Qiang & Chaoran Yu. (2020). Association between liver targeted antiviral therapy in colorectal cancer and survival benefits: An appraisal. World Journal of Clinical Cases. 8(11). 2111–2115. 2 indexed citations
11.
Yu, Chaoran & Yujie Zhang. (2020). Establishment of prognostic nomogram for elderly colorectal cancer patients: a SEER database analysis. BMC Gastroenterology. 20(1). 347–347. 36 indexed citations
12.
Yu, Chaoran & Yujie Zhang. (2019). Development and validation of prognostic nomogram for young patients with gastric cancer. Annals of Translational Medicine. 7(22). 641–641. 70 indexed citations
13.
Yu, Chaoran & Yujie Zhang. (2019). Characterization of the prognostic values of CXCR family in gastric cancer. Cytokine. 123. 154785–154785. 19 indexed citations
14.
Yu, Chaoran, Jie Chen, Junjun Ma, et al.. (2019). Identification of Key Genes and Signaling Pathways Associated with the Progression of Gastric Cancer. Pathology & Oncology Research. 26(3). 1903–1919. 21 indexed citations
15.
Zhang, Sen, Chaoran Yu, Xiao Yang, et al.. (2019). N-myc downstream-regulated gene 1 inhibits the proliferation of colorectal cancer through emulative antagonizing NEDD4-mediated ubiquitylation of p21. Journal of Experimental & Clinical Cancer Research. 38(1). 490–490. 41 indexed citations
16.
Yu, Chaoran, Pei Xue, Luyang Zhang, et al.. (2018). Prediction of key genes and pathways involved in trastuzumab-resistant gastric cancer. World Journal of Surgical Oncology. 16(1). 174–174. 19 indexed citations
17.
Xie, Daxing, Chaoran Yu, Liang Liu, et al.. (2016). Short-term outcomes of laparoscopic D2 lymphadenectomy with complete mesogastrium excision for advanced gastric cancer. Surgical Endoscopy. 30(11). 5138–5139. 24 indexed citations
18.
Xie, Daxing, et al.. (2016). An Optimal Approach for Laparoscopic D3 Lymphadenectomy Plus Complete Mesocolic Excision (D3+CME) for Right-Sided Colon Cancer. Annals of Surgical Oncology. 24(5). 1312–1313. 31 indexed citations
19.
Xie, Daxing, Liang Liu, Chaoran Yu, et al.. (2015). Detection and Characterization of Metastatic Cancer Cells in the Mesogastrium of Gastric Cancer Patients. PLoS ONE. 10(11). e0142970–e0142970. 23 indexed citations
20.
Xie, Daxing, Chun Gao, Liang Liu, et al.. (2015). Proximal segmentation of the dorsal mesogastrium reveals new anatomical implications for laparoscopic surgery. Scientific Reports. 5(1). 16287–16287. 19 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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