Mei‐Jie Zhang

4.1k total citations
112 papers, 2.5k citations indexed

About

Mei‐Jie Zhang is a scholar working on Hematology, Public Health, Environmental and Occupational Health and Statistics and Probability. According to data from OpenAlex, Mei‐Jie Zhang has authored 112 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Hematology, 30 papers in Public Health, Environmental and Occupational Health and 27 papers in Statistics and Probability. Recurrent topics in Mei‐Jie Zhang's work include Hematopoietic Stem Cell Transplantation (37 papers), Acute Lymphoblastic Leukemia research (28 papers) and Statistical Methods and Inference (26 papers). Mei‐Jie Zhang is often cited by papers focused on Hematopoietic Stem Cell Transplantation (37 papers), Acute Lymphoblastic Leukemia research (28 papers) and Statistical Methods and Inference (26 papers). Mei‐Jie Zhang collaborates with scholars based in United States, China and Canada. Mei‐Jie Zhang's co-authors include Thomas Scheike, John P. Klein, Per Kragh Andersen, Xu Zhang, Fausto R. Loberiza, Brent R. Logan, Xu Zhang, Jason P. Fine, Mary M. Horowitz and Hillard M. Lazarus and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Mei‐Jie Zhang

107 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mei‐Jie Zhang United States 28 674 454 449 427 304 112 2.5k
Liesbeth C. de Wreede Netherlands 20 648 1.0× 384 0.8× 166 0.4× 252 0.6× 182 0.6× 65 1.7k
Dennis O. Dixon United States 29 785 1.2× 864 1.9× 242 0.5× 337 0.8× 795 2.6× 76 2.6k
Kaspar Rufibach Switzerland 33 272 0.4× 657 1.4× 369 0.8× 129 0.3× 638 2.1× 110 3.4k
Carin A. Uyl‐de Groot Netherlands 34 512 0.8× 1.5k 3.2× 91 0.2× 383 0.9× 368 1.2× 217 3.7k
Eisuke Inoue Japan 39 782 1.2× 509 1.1× 202 0.4× 275 0.6× 791 2.6× 233 5.5k
Sandra Eloranta Sweden 31 514 0.8× 957 2.1× 101 0.2× 403 0.9× 635 2.1× 125 3.1k
Ileana Baldi Italy 25 431 0.6× 490 1.1× 74 0.2× 232 0.5× 140 0.5× 112 2.1k
Kannan Natarajan United States 14 339 0.5× 169 0.4× 135 0.3× 119 0.3× 130 0.4× 23 2.3k
Rahul Mhaskar United States 23 374 0.6× 693 1.5× 54 0.1× 225 0.5× 156 0.5× 150 2.0k
Jeremy Millar Australia 37 401 0.6× 1.6k 3.5× 119 0.3× 326 0.8× 176 0.6× 294 6.5k

Countries citing papers authored by Mei‐Jie Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Mei‐Jie Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mei‐Jie Zhang. 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 Mei‐Jie Zhang. The network helps show where Mei‐Jie Zhang may publish in the future.

Co-authorship network of co-authors of Mei‐Jie Zhang

This figure shows the co-authorship network connecting the top 25 collaborators of Mei‐Jie Zhang. A scholar is included among the top collaborators of Mei‐Jie Zhang 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 Mei‐Jie Zhang. Mei‐Jie Zhang 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.
Song, Ge, Mei‐Jie Zhang, Weida Liu, & Guanzhao Liang. (2023). Children onychomycosis, a neglected dermatophytosis: A retrospective study of epidemiology and treatment. Mycoses. 66(5). 448–454. 4 indexed citations
3.
Abid, Muhammad Bilal, Noel Estrada‐Merly, Mei‐Jie Zhang, et al.. (2023). Impact of Donor Age on Allogeneic Hematopoietic Cell Transplantation Outcomes in Older Adults with Acute Myeloid Leukemia. Transplantation and Cellular Therapy. 29(9). 578.e1–578.e9. 9 indexed citations
4.
5.
Dai, Ran, Cheng Zheng, & Mei‐Jie Zhang. (2022). On High-Dimensional Covariate Adjustment for Estimating Causal Effects in Randomized Trials with Survival Outcomes. Statistics in Biosciences. 15(1). 242–260.
6.
Song, Ge, Mei‐Jie Zhang, Weida Liu, & Guanzhao Liang. (2022). Epidemiology of Onychomycosis in Chinese Mainland: A 30-year Retrospective Study. Mycopathologia. 187(4). 323–331. 12 indexed citations
7.
O’Donnell, Paul V., Claudio G. Brunstein, Ephraim J. Fuchs, et al.. (2021). Umbilical Cord Blood or HLA-Haploidentical Transplantation: Real-World Outcomes versus Randomized Trial Outcomes. Transplantation and Cellular Therapy. 28(2). 109.e1–109.e8. 10 indexed citations
8.
Liang, Guanzhao, et al.. (2020). Adult tinea capitis in China: A retrospective analysis from 2000 to 2019. Mycoses. 63(8). 876–888. 28 indexed citations
9.
10.
Keesler, Daniel A., Andrew St. Martin, Carmem Bonfim, et al.. (2018). Bone Marrow versus Peripheral Blood from Unrelated Donors for Children and Adolescents with Acute Leukemia. Biology of Blood and Marrow Transplantation. 24(12). 2487–2492. 12 indexed citations
11.
Zheng, Cheng, Ran Dai, Parameswaran Hari, & Mei‐Jie Zhang. (2017). Instrumental variable with competing risk model. Statistics in Medicine. 36(8). 1240–1255. 9 indexed citations
12.
Strouse, Christopher, Ying Zhang, Mei‐Jie Zhang, et al.. (2017). Stratification of Allogeneic Hematopoietic Cell Transplant Patients by Risk of Developing Veno-Occlusive Disease: A Model for Assigning a Risk Score. Biology of Blood and Marrow Transplantation. 23(3). S302–S303. 2 indexed citations
13.
Eriksson, Frank, Jianing Li, Thomas Scheike, & Mei‐Jie Zhang. (2015). The proportional odds cumulative incidence model for competing risks. Biometrics. 71(3). 687–695. 24 indexed citations
14.
He, Peng, Frank Eriksson, Thomas Scheike, & Mei‐Jie Zhang. (2015). A Proportional Hazards Regression Model for the Subdistribution with Covariates‐adjusted Censoring Weight for Competing Risks Data. Scandinavian Journal of Statistics. 43(1). 103–122. 47 indexed citations
15.
Hitzler, Johann, Wensheng He, John Doyle, et al.. (2014). Outcome of transplantation for acute lymphoblastic leukemia in children with down syndrome. Pediatric Blood & Cancer. 61(6). 1126–1128. 26 indexed citations
16.
Scheike, Thomas & Mei‐Jie Zhang. (2011). Analyzing Competing Risk Data Using the R timereg Package. SHILAP Revista de lepidopterología. 9 indexed citations
17.
Scheike, Thomas & Mei‐Jie Zhang. (2008). Flexible competing risks regression modeling and goodness-of-fit. Lifetime Data Analysis. 14(4). 464–483. 68 indexed citations
18.
Miller, Carole B., Philip A. Rowlings, Mei‐Jie Zhang, et al.. (2001). The effect of graft purging with 4-hydroperoxycyclophosphamide in autologous bone marrow transplantation for acute myelogenous leukemia. Experimental Hematology. 29(11). 1336–1346. 37 indexed citations
19.
Zhang, Mei‐Jie, Michele Baccarani, Robert Peter Gale, et al.. (1997). Survival of patients with chronic myelogenous leukaemia relapsing after bone marrow transplantation: comparison with patients receiving conventional chemotherapy. British Journal of Haematology. 99(1). 23–29. 2 indexed citations
20.
Horowitz, M., Philip A. Rowlings, Mei‐Jie Zhang, et al.. (1994). Bone Marrow Transplantation—1994: A Report from the International Bone Marrow Transplant Registry and the North American Autologous Bone Marrow Transplant Registry. Journal of Hematotherapy. 3(2). 95–102. 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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