Hai Li
Impact in
- Hepatology top 10%
- Liver Disease and Transplantation
- Hepatitis C virus research
- Hepatitis Viruses Studies and Epidemiology
-
- Drug-Induced Hepatotoxicity and Protection
Papers in
-
- Liver Disease and Transplantation 7
- Hepatocellular Carcinoma Treatment and Prognosis 1
-
- Liver Disease Diagnosis and Treatment 3
- Co-authors
- Yongping Chen (1 shared paper)Keqing Shi (1 shared paper)Ming‐Hua Zheng (1 shared paper)Wen Gu (4 shared papers)Shan Yin (2 shared papers)Yan Zhang (3 shared papers)Baoyan Xu (2 shared papers)Xianbo Wang (3 shared papers)
- Journals
- Scientific Reports (1 paper)BMC Cancer (1 paper)Computerized Medical Imaging and Graphics (1 paper)Clinical Gastroenterology and Hepatology (1 paper)npj Precision Oncology (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Hai Li
13 papers receiving 168 citations
Peers
Comparison fields: 5 of 31
- Hepatology 99
- Pharmacology 21
- Epidemiology 68
- Health Informatics 1
- Endocrinology, Diabetes and Metabolism 8
Countries citing papers authored by Hai Li
This map shows the geographic impact of Hai Li'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 Hai Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hai Li more than expected).
Fields of papers citing papers by Hai Li
This network shows the impact of papers produced by Hai Li. 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 Hai Li. The network helps show where Hai Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Hai Li, 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 | 2011 | 60 | |
| 2 | 2018 | 32 | |
| 3 | 2017 | 18 | |
| 4 | 2013 | 17 | |
| 5 | 2021 | 15 | |
| 6 | 2021 | 6 | |
| 7 | 2024 | 5 | |
| 8 | 2025 | 5 | |
| 9 | 2018 | 4 | |
| 10 | 2025 | 3 | |
| 11 | 2025 | 2 | |
| 12 | 2025 | 2 | |
| 13 | 2025 | 1 | |
| 14 | 2025 | 0 |
About Hai Li
Hai Li is a scholar working on Hepatology, Epidemiology, Radiology, Nuclear Medicine and Imaging, Surgery and Artificial Intelligence, having authored 14 papers that have together received 170 indexed citations. Recurring topics across this work include Liver Disease and Transplantation (7 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Liver Disease Diagnosis and Treatment (3 papers), Thyroid Cancer Diagnosis and Treatment (2 papers), AI in cancer detection (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Ferroptosis and cancer prognosis (1 paper) and Urinary Bladder and Prostate Research (1 paper). The work is most often cited by research in Hepatology (99 citations), Pharmacology (21 citations), Epidemiology (68 citations), Health Informatics (1 citation) and Endocrinology, Diabetes and Metabolism (8 citations). Hai Li has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Yongping Chen, Keqing Shi, Ming‐Hua Zheng, Wen Gu, Shan Yin, Yan Zhang, Baoyan Xu, Xianbo Wang, Shaoyang Wang and Xin Zheng. Their work appears in journals such as Scientific Reports, BMC Cancer, Computerized Medical Imaging and Graphics, Clinical Gastroenterology and Hepatology and npj Precision Oncology.
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.