Chaoling Feng

1.1k total citations
25 papers, 225 citations indexed

About

Chaoling Feng is a scholar working on Oncology, Economics and Econometrics and Pathology and Forensic Medicine. According to data from OpenAlex, Chaoling Feng has authored 25 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Oncology, 8 papers in Economics and Econometrics and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Chaoling Feng's work include CAR-T cell therapy research (9 papers), Lymphoma Diagnosis and Treatment (6 papers) and Acute Lymphoblastic Leukemia research (4 papers). Chaoling Feng is often cited by papers focused on CAR-T cell therapy research (9 papers), Lymphoma Diagnosis and Treatment (6 papers) and Acute Lymphoblastic Leukemia research (4 papers). Chaoling Feng collaborates with scholars based in United States, United Kingdom and Brazil. Chaoling Feng's co-authors include Binwu Sheng, Donglan Zhang, Lu Shi, Hugh Spitler, Lane Koenig, Berna Demiralp, Jennifer T. Nguyen, Matthew S. Austin, Thomas K. Fehring and Qian Zhang and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Gastroenterology.

In The Last Decade

Chaoling Feng

23 papers receiving 212 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chaoling Feng United States 8 82 64 47 44 36 25 225
Frane Grubišić Croatia 11 29 0.4× 47 0.7× 22 0.5× 31 0.7× 20 0.6× 52 324
Neha Chopra United Kingdom 8 29 0.4× 38 0.6× 75 1.6× 25 0.6× 24 0.7× 19 210
Rosemar Macedo Sousa Rahal Brazil 11 40 0.5× 45 0.7× 111 2.4× 4 0.1× 53 1.5× 33 276
Samantha E. Hoffman United States 7 26 0.3× 21 0.3× 27 0.6× 12 0.3× 23 0.6× 26 152
Yue Zheng United States 11 54 0.7× 22 0.3× 180 3.8× 14 0.3× 60 1.7× 42 352
Jean-Paul Larbre France 8 45 0.5× 27 0.4× 23 0.5× 15 0.3× 6 0.2× 25 287
Jessica Stoll United States 10 210 2.6× 288 4.5× 87 1.9× 42 1.0× 23 0.6× 16 430
Simon Tso United Kingdom 6 17 0.2× 32 0.5× 40 0.9× 6 0.1× 23 0.6× 41 152
Debin Wang China 9 45 0.5× 8 0.1× 107 2.3× 16 0.4× 22 0.6× 20 220
Marie Todd United Kingdom 12 180 2.2× 36 0.6× 216 4.6× 5 0.1× 21 0.6× 52 349

Countries citing papers authored by Chaoling Feng

Since Specialization
Citations

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

Fields of papers citing papers by Chaoling Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chaoling Feng

This figure shows the co-authorship network connecting the top 25 collaborators of Chaoling Feng. A scholar is included among the top collaborators of Chaoling Feng 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 Chaoling Feng. Chaoling Feng 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
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Ahmed, Nausheen, Fang Sun, Christie Teigland, et al.. (2024). Chimeric Antigen Receptor T-Cell Access in Patients with Relapsed/Refractory Large B-Cell Lymphoma: Association of Access with Social Determinants of Health and Travel Time to Treatment Centers. Transplantation and Cellular Therapy. 30(7). 714–725. 9 indexed citations
3.
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Oluwole, Olalekan O., Anik R. Patel, Nathaniel Smith, et al.. (2023). An updated cost-effectiveness analysis of axicabtagene ciloleucel in second-line large B-cell lymphoma patients in the United States. Journal of Medical Economics. 27(1). 77–83. 8 indexed citations
5.
Shah, Bijal, James J. Wu, Chaoling Feng, et al.. (2023). Matching-Adjusted Indirect Comparisons of Brexucabtagene Autoleucel with Alternative Standard Therapies for Relapsed/Refractory B-Cell Acute Lymphoblastic Leukemia in Adult Patients. Advances in Therapy. 40(12). 5383–5398. 1 indexed citations
6.
Shah, Bijal, Nathaniel Smith, Chaoling Feng, et al.. (2022). Cost-Effectiveness of KTE-X19 for Adults with Relapsed/Refractory B-Cell Acute Lymphoblastic Leukemia in the United States. Advances in Therapy. 39(8). 3678–3695. 6 indexed citations
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Shah, Bijal, Nathaniel Smith, Chaoling Feng, et al.. (2021). ALL-190: Cost-Effectiveness of KTE-X19 for Adult Patients with Relapsed/Refractory B-Cell Acute Lymphoblastic Leukemia (R/R B-ALL) in the United States. Clinical Lymphoma Myeloma & Leukemia. 21. S272–S273. 1 indexed citations
10.
Demiralp, Berna, et al.. (2019). <p>Length of stay, mortality, and readmissions among Medicare cancer patients treated with glucarpidase and conventional care: a retrospective study</p>. ClinicoEconomics and Outcomes Research. Volume 11. 129–144. 17 indexed citations
11.
Francis, Ellen C., et al.. (2019). Association Between Prior Insurance and Health Service Utilization Among the Long-Term Uninsured in South Carolina. Health Equity. 3(1). 409–416. 1 indexed citations
12.
Koenig, Lane, Chaoling Feng, Fang He, & Jennifer T. Nguyen. (2018). The Effects of Revision Total Hip Arthroplasty on Medicare Spending and Beneficiary Outcomes: Implications for the Comprehensive Care for Joint Replacement Model. The Journal of Arthroplasty. 33(9). 2764–2769.e2. 11 indexed citations
13.
Gilligan, Adrienne M., et al.. (2018). Healthcare resource utilization (HRU) and costs associated with renal impairment (RI) among treated multiple myeloma (MM) patients.. Journal of Clinical Oncology. 36(15_suppl). e18922–e18922.
14.
Osterman, Mark T., Millie D. Long, Siddharth Singh, et al.. (2018). Sa1711 - Real World Comparative Risk of Serious Infection with Adalimumab, Vedolizumab, and Infliximab in Patients with Inflammatory Bowel Disease. Gastroenterology. 154(6). S–365. 2 indexed citations
15.
Sheng, Binwu, Chaoling Feng, Donglan Zhang, Hugh Spitler, & Lu Shi. (2017). Associations between Obesity and Spinal Diseases: A Medical Expenditure Panel Study Analysis. International Journal of Environmental Research and Public Health. 14(2). 183–183. 67 indexed citations
16.
Feng, Chaoling, et al.. (2017). Does Awareness of the Affordable Care Act Reduce Adverse Selection? A Study of the Long-term Uninsured in South Carolina. INQUIRY The Journal of Health Care Organization Provision and Financing. 54. 1140279935–1140279935. 3 indexed citations
17.
Koenig, Lane, Qian Zhang, Matthew S. Austin, et al.. (2016). Estimating the Societal Benefits of THA After Accounting for Work Status and Productivity: A Markov Model Approach. Clinical Orthopaedics and Related Research. 474(12). 2645–2654. 48 indexed citations
18.
Perry, Walter L., et al.. (2016). Defense Institution Building: An Assessment. RAND Corporation eBooks. 2 indexed citations
19.
Pézard, Stéphanie, et al.. (2016). Defense Institution Building in Africa: An Assessment. RAND Corporation eBooks. 11 indexed citations
20.
Kalra, Nidhi, Obaid Younossi, Gary Cecchine, et al.. (2011). Recommended Research Priorities for the Qatar Foundation's Environment and Energy Research Institute. 6 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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