Wei Han
Impact in
- Hematology top 0.2%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
- Chronic Myeloid Leukemia Treatments
- Transplantation top 2%
Papers in
- Hematology 70
- Hematopoietic Stem Cell Transplantation 60
- Acute Myeloid Leukemia Research 28
- Chronic Myeloid Leukemia Treatments 10
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- Acute Lymphoblastic Leukemia research 31
- Co-authors
- Xiao‐Jun Huang (77 shared papers)Lan‐Ping Xu (76 shared papers)Kai‐Yan Liu (65 shared papers)Huan Chen (57 shared papers)Yu Wang (62 shared papers)Xiaohui Zhang (62 shared papers)Yu‐Hong Chen (68 shared papers)Dai‐Hong Liu (23 shared papers)
- Journals
- Biology of Blood and Marrow Transplantation (19 papers)Blood (10 papers)Bone Marrow Transplantation (7 papers)British Journal of Haematology (5 papers)Clinical Transplantation (5 papers)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Wei Han
157 papers receiving 3.0k citations
Peers
Comparison fields: 5 of 146
- Hematology 2.2k
- Transplantation 178
- Immunology 887
- Genetics 324
- Oncology 720
Countries citing papers authored by Wei Han
This map shows the geographic impact of Wei Han'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 Wei Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Han more than expected).
Fields of papers citing papers by Wei Han
This network shows the impact of papers produced by Wei Han. 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 Wei Han. The network helps show where Wei Han may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 180 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 394 | |
| 2 | 2014 | 241 | |
| 3 | 2012 | 236 | |
| 4 | 2009 | 233 | |
| 5 | 2015 | 148 | |
| 6 | 2013 | 105 | |
| 7 | 2012 | 96 | |
| 8 | 2008 | 61 | |
| 9 | 2012 | 56 | |
| 10 | 2011 | 56 | |
| 11 | 2022 | 52 | |
| 12 | 2013 | 49 | |
| 13 | 2017 | 48 | |
| 14 | 2014 | 48 | |
| 15 | 2019 | 45 | |
| 16 | 2015 | 44 | |
| 17 | 2016 | 44 | |
| 18 | 2020 | 38 | |
| 19 | 2017 | 37 | |
| 20 | 2012 | 33 |
About Wei Han
Wei Han is a scholar working on Hematology, Public Health, Environmental and Occupational Health, Oncology, Immunology and Pulmonary and Respiratory Medicine, having authored 180 papers that have together received 3.1k indexed citations. Recurring topics across this work include Hematopoietic Stem Cell Transplantation (60 papers), Acute Lymphoblastic Leukemia research (31 papers), Acute Myeloid Leukemia Research (28 papers), Polyomavirus and related diseases (13 papers), Chronic Myeloid Leukemia Treatments (10 papers), T-cell and B-cell Immunology (9 papers), Immune Cell Function and Interaction (8 papers) and Radiomics and Machine Learning in Medical Imaging (6 papers). The work is most often cited by research in Hematology (2.2k citations), Transplantation (178 citations), Immunology (887 citations), Genetics (324 citations) and Oncology (720 citations). Wei Han has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Xiao‐Jun Huang, Lan‐Ping Xu, Kai‐Yan Liu, Huan Chen, Yu Wang, Xiaohui Zhang, Yu‐Hong Chen, Dai‐Hong Liu, Chen‐Hua Yan and Feng‐Rong Wang. Their work appears in journals such as Biology of Blood and Marrow Transplantation, Blood, Bone Marrow Transplantation, British Journal of Haematology and Clinical Transplantation.
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.