Bi‐Ling Liang
- Biomaterials top 5%
- Nanoparticle-Based Drug Delivery 7
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- MRI in cancer diagnosis 10
- Radiomics and Machine Learning in Medical Imaging 7
- Advanced MRI Techniques and Applications 5
- Obstetrics and Gynecology top 5%
- Genetics top 10%
- Molecular Medicine top 10%
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- Head and Neck Cancer Studies 7
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- Hepatocellular Carcinoma Treatment and Prognosis 6
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- Sarcoma Diagnosis and Treatment 5
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- Liver Disease Diagnosis and Treatment 4
- Journals
- Journal of Magnetic Resonance Imaging (6 papers)European Journal of Radiology (5 papers)Journal of Materials Chemistry (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Bi‐Ling Liang
54 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 90
- Biomaterials 263
- Radiology, Nuclear Medicine and Imaging 326
- Obstetrics and Gynecology 110
- Genetics 102
- Molecular Medicine 45
Countries citing papers authored by Bi‐Ling Liang
This map shows the geographic impact of Bi‐Ling Liang'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 Bi‐Ling Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bi‐Ling Liang more than expected).
Fields of papers citing papers by Bi‐Ling Liang
This network shows the impact of papers produced by Bi‐Ling Liang. 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 Bi‐Ling Liang. The network helps show where Bi‐Ling Liang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Bi‐Ling Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2020 | 11 | |
| 3 | 2013 | 5 | |
| 4 | 2012 | 30 | |
| 5 | 2012 | 10 | |
| 6 | 2011 | 23 | |
| 7 | 2011 | 8 | |
| 8 | 2010 | 78 | |
| 9 | 2010 | 43 | |
| 10 | 2010 | 30 | |
| 11 | 2010 | 23 | |
| 12 | 2009 | 12 | |
| 13 | 2009 | 52 | |
| 14 | 2009 | 17 | |
| 15 | 2009 | 119 | |
| 16 | 2008 | 1 | |
| 17 | 2008 | 4 | |
| 18 | 2008 | 97 | |
| 19 | 2008 | 79 | |
| 20 | 2007 | 6 |
About Bi‐Ling Liang
Bi‐Ling Liang is a scholar working on Otorhinolaryngology, Hepatology and Radiology, Nuclear Medicine and Imaging, having authored 56 papers that have together received 1.1k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (10 papers), Nanoparticle-Based Drug Delivery (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Head and Neck Cancer Studies (7 papers), Hepatocellular Carcinoma Treatment and Prognosis (6 papers), Advanced MRI Techniques and Applications (5 papers), Sarcoma Diagnosis and Treatment (5 papers) and Liver Disease Diagnosis and Treatment (4 papers). The work is most often cited by research in Biomaterials (263 citations), Radiology, Nuclear Medicine and Imaging (326 citations) and Obstetrics and Gynecology (110 citations). Bi‐Ling Liang has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Jun Shen, Jianyu Chen, Xintao Shuai, Zehong Yang, Yun Zhang, Qingyu Liu, Qiquan Sun, Guobin Hong, Renxu Yuan and Chengde Liao. Their work appears in journals such as Journal of Magnetic Resonance Imaging, European Journal of Radiology, Journal of Materials Chemistry, International Journal of Nanomedicine and Gene.
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.