Hao Xi
Impact in
- Hematology top 10%
- Multiple Myeloma Research and Treatments
-
- MicroRNA in disease regulation
Papers in
-
- Advanced Neural Network Applications 6
- Video Surveillance and Tracking Methods 3
- Hematology 11
- Multiple Myeloma Research and Treatments 10
- Co-authors
- Jian Hou (8 shared papers)Weijun Fu (14 shared papers)Micol Spitale (2 shared papers)Maja J. Matarić (2 shared papers)Juan Du (5 shared papers)Shuyan Liu (1 shared paper)Jie He (1 shared paper)Wenqing Yan (1 shared paper)
- Journals
- Expert Systems with Applications (3 papers)Oncotarget (2 papers)Applied Intelligence (2 papers)Frontiers in Earth Science (1 paper)Blood (1 paper)
- Partner nations
- ChinaUnited StatesItaly
In The Last Decade
Hao Xi
38 papers receiving 355 citations
Peers
Comparison fields: 5 of 98
- Hematology 72
- Cancer Research 47
- Molecular Biology 164
- Oncology 51
- Pathology and Forensic Medicine 33
Countries citing papers authored by Hao Xi
This map shows the geographic impact of Hao Xi'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 Hao Xi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hao Xi more than expected).
Fields of papers citing papers by Hao Xi
This network shows the impact of papers produced by Hao Xi. 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 Hao Xi. The network helps show where Hao Xi may publish in the future.
Co-authors
The 25 scholars most cited alongside Hao Xi, 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 47 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 85 | |
| 2 | 2014 | 37 | |
| 3 | 2022 | 30 | |
| 4 | 2022 | 24 | |
| 5 | 2016 | 20 | |
| 6 | 2021 | 18 | |
| 7 | 2019 | 17 | |
| 8 | 2009 | 12 | |
| 9 | 2021 | 11 | |
| 10 | 2020 | 11 | |
| 11 | 2017 | 10 | |
| 12 | 2016 | 10 | |
| 13 | 2021 | 9 | |
| 14 | Clinical features of multiple myeloma invasion of the central nervous system in Chinese patients. | 2010 | 9 |
| 15 | 2021 | 9 | |
| 16 | 2015 | 6 | |
| 17 | 2024 | 5 | |
| 18 | 2013 | 5 | |
| 19 | [Bortezomib in combination with dexamethasone for the treatment of relapsed or refractory multiple myeloma]. | 2006 | 4 |
| 20 | 2024 | 4 |
About Hao Xi
Hao Xi is a scholar working on Computer Vision and Pattern Recognition, Hematology, Artificial Intelligence, Molecular Biology and Biomedical Engineering, having authored 47 papers that have together received 362 indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (10 papers), Advanced Neural Network Applications (6 papers), Domain Adaptation and Few-Shot Learning (4 papers), Gait Recognition and Analysis (4 papers), EEG and Brain-Computer Interfaces (3 papers), Video Surveillance and Tracking Methods (3 papers), ECG Monitoring and Analysis (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Hematology (72 citations), Cancer Research (47 citations), Molecular Biology (164 citations), Oncology (51 citations) and Pathology and Forensic Medicine (33 citations). Hao Xi has collaborated with scholars based in China, United States and Italy. Frequent co-authors include Jian Hou, Weijun Fu, Micol Spitale, Maja J. Matarić, Juan Du, Shuyan Liu, Jie He, Wenqing Yan, Rong Li and Xi Liu. Their work appears in journals such as Expert Systems with Applications, Oncotarget, Applied Intelligence, Frontiers in Earth Science and Blood.
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.