Jeff Dai
Impact in
- Hepatology top 2%
- Hepatocellular Carcinoma Treatment and Prognosis
- Liver Disease and Transplantation
- Hepatitis C virus research
- Liver physiology and pathology
- Epidemiology top 10%
- Liver Disease Diagnosis and Treatment
- Hepatitis B Virus Studies
Papers in
- Hepatology 14
- Liver Disease and Transplantation 9
- Hepatocellular Carcinoma Treatment and Prognosis 8
- Surgery 13
- Organ Transplantation Techniques and Outcomes 10
- Cholangiocarcinoma and Gallbladder Cancer Studies 4
- Co-authors
- Albert Chan (15 shared papers)Ksh Chok (12 shared papers)Chung Mau Lo (9 shared papers)Tan To Cheung (13 shared papers)Tiffany Wong (9 shared papers)James Fung (8 shared papers)Kelvin K. Ng (6 shared papers)Chung‐Mau Lo (6 shared papers)
- Journals
- Hepatology (3 papers)Annals of Surgery (3 papers)Surgery (2 papers)Journal of Hepatology (1 paper)Journal of Pharmaceutical Innovation (1 paper)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Jeff Dai
19 papers receiving 487 citations
Peers
Comparison fields: 5 of 46
- Hepatology 415
- Epidemiology 265
- Transplantation 14
- Surgery 224
- Oncology 53
Countries citing papers authored by Jeff Dai
This map shows the geographic impact of Jeff Dai'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 Jeff Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Dai more than expected).
Fields of papers citing papers by Jeff Dai
This network shows the impact of papers produced by Jeff Dai. 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 Jeff Dai. The network helps show where Jeff Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Jeff Dai, 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 | 2019 | 89 | |
| 2 | 2017 | 71 | |
| 3 | 2015 | 47 | |
| 4 | 2016 | 47 | |
| 5 | 2019 | 41 | |
| 6 | 2019 | 40 | |
| 7 | 2021 | 38 | |
| 8 | 2020 | 29 | |
| 9 | 2020 | 22 | |
| 10 | 2019 | 17 | |
| 11 | 2020 | 15 | |
| 12 | 2016 | 11 | |
| 13 | 2014 | 7 | |
| 14 | 2020 | 7 | |
| 15 | 2018 | 5 | |
| 16 | 2018 | 4 | |
| 17 | 2018 | 2 | |
| 18 | 2018 | 2 | |
| 19 | 2018 | 1 | |
| 20 | 2020 | 0 |
About Jeff Dai
Jeff Dai is a scholar working on Hepatology, Surgery, Epidemiology, Oncology and Public Health, Environmental and Occupational Health, having authored 20 papers that have together received 495 indexed citations. Recurring topics across this work include Organ Transplantation Techniques and Outcomes (10 papers), Liver Disease and Transplantation (9 papers), Hepatocellular Carcinoma Treatment and Prognosis (8 papers), Liver Disease Diagnosis and Treatment (4 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (4 papers), Organ Donation and Transplantation (2 papers), Hepatitis B Virus Studies (2 papers) and Semiconductor materials and interfaces (1 paper). The work is most often cited by research in Hepatology (415 citations), Epidemiology (265 citations), Transplantation (14 citations), Surgery (224 citations) and Oncology (53 citations). Jeff Dai has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Albert Chan, Ksh Chok, Chung Mau Lo, Tan To Cheung, Tiffany Wong, James Fung, Kelvin K. Ng, Chung‐Mau Lo, Ronnie T. P. Poon and Crystal Kwan. Their work appears in journals such as Hepatology, Annals of Surgery, Surgery, Journal of Hepatology and Journal of Pharmaceutical Innovation.
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.