Ming-Da Wang
Impact in
- Hepatology top 1%
- Hepatocellular Carcinoma Treatment and Prognosis
- Cancer Research top 10%
- Cancer, Lipids, and Metabolism
- Cancer, Hypoxia, and Metabolism
Papers in
- Hepatology 41
- Hepatocellular Carcinoma Treatment and Prognosis 40
-
- Cancer, Lipids, and Metabolism 5
- Cancer, Hypoxia, and Metabolism 5
- Co-authors
- Tian Yang (38 shared papers)Feng Shen (39 shared papers)Wan Yee Lau (32 shared papers)Lei Liang (21 shared papers)Han Wu (26 shared papers)Mengchao Wu (16 shared papers)Timothy M. Pawlik (22 shared papers)Chao Li (20 shared papers)
- Journals
- Annals of Surgical Oncology (5 papers)HPB (4 papers)Journal of Gastrointestinal Surgery (4 papers)Advanced Materials (3 papers)Surgery (3 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Ming-Da Wang
71 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 85
- Hepatology 604
- Cancer Research 242
- Epidemiology 218
- Oncology 167
- Molecular Biology 234
Countries citing papers authored by Ming-Da Wang
This map shows the geographic impact of Ming-Da Wang'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 Ming-Da Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming-Da Wang more than expected).
Fields of papers citing papers by Ming-Da Wang
This network shows the impact of papers produced by Ming-Da Wang. 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 Ming-Da Wang. The network helps show where Ming-Da Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming-Da Wang, 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 79 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 84 | |
| 2 | 2016 | 69 | |
| 3 | 2019 | 59 | |
| 4 | 2019 | 59 | |
| 5 | 2017 | 50 | |
| 6 | 2018 | 50 | |
| 7 | 2022 | 49 | |
| 8 | 2016 | 48 | |
| 9 | 2018 | 43 | |
| 10 | 2022 | 41 | |
| 11 | 2019 | 37 | |
| 12 | 2019 | 36 | |
| 13 | 2021 | 34 | |
| 14 | 2021 | 34 | |
| 15 | 2018 | 32 | |
| 16 | 2021 | 27 | |
| 17 | 2022 | 26 | |
| 18 | 2024 | 25 | |
| 19 | 2022 | 22 | |
| 20 | 2018 | 21 |
About Ming-Da Wang
Ming-Da Wang is a scholar working on Hepatology, Cancer Research, Molecular Biology, Oncology and Epidemiology, having authored 79 papers that have together received 1.3k indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (40 papers), Liver Disease Diagnosis and Treatment (5 papers), Cancer, Lipids, and Metabolism (5 papers), Nanoplatforms for cancer theranostics (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers), Hepatitis B Virus Studies (3 papers) and Cancer Immunotherapy and Biomarkers (3 papers). The work is most often cited by research in Hepatology (604 citations), Cancer Research (242 citations), Epidemiology (218 citations), Oncology (167 citations) and Molecular Biology (234 citations). Ming-Da Wang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Tian Yang, Feng Shen, Wan Yee Lau, Lei Liang, Han Wu, Mengchao Wu, Timothy M. Pawlik, Chao Li, Hao Xing and Ting‐Hao Chen. Their work appears in journals such as Annals of Surgical Oncology, HPB, Journal of Gastrointestinal Surgery, Advanced Materials and Surgery.
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.