Dun Jack Fu
Impact in
- Health Informatics top 0.1%
- Artificial Intelligence in Healthcare and Education
- Ophthalmology top 1%
- Retinal Diseases and Treatments
- Retinal and Optic Conditions
- Glaucoma and retinal disorders
Papers in
-
- Retinal Diseases and Treatments 16
- Glaucoma and retinal disorders 5
- Retinal and Optic Conditions 3
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- Retinal Imaging and Analysis 7
- COVID-19 diagnosis using AI 2
- Radiomics and Machine Learning in Medical Imaging 1
- Co-authors
- Pearse A. Keane (29 shared papers)Siegfried K. Wagner (23 shared papers)Konstantinos Balaskas (26 shared papers)Livia Faes (24 shared papers)Alastair K. Denniston (7 shared papers)Xiaoxuan Liu (7 shared papers)Gabriella Moraes (14 shared papers)Lucas M. Bachmann (8 shared papers)
- Journals
- British Journal of Ophthalmology (6 papers)Eye (4 papers)The Lancet Digital Health (4 papers)BMJ Open Ophthalmology (3 papers)Translational Vision Science & Technology (3 papers)
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Dun Jack Fu
41 papers receiving 2.2k citations
Dun Jack Fu's Hit Papers
Peers
Comparison fields: 5 of 148
- Health Informatics 496
- Ophthalmology 505
- Radiology, Nuclear Medicine and Imaging 829
- Health Information Management 105
- Artificial Intelligence 409
Countries citing papers authored by Dun Jack Fu
This map shows the geographic impact of Dun Jack Fu'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 Dun Jack Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dun Jack Fu more than expected).
Fields of papers citing papers by Dun Jack Fu
This network shows the impact of papers produced by Dun Jack Fu. 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 Dun Jack Fu. The network helps show where Dun Jack Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dun Jack Fu, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis Hit paper breakdown → | 2019 | 1073 |
| 2 | 2019 | 207 | |
| 3 | 2020 | 159 | |
| 4 | 2020 | 115 | |
| 5 | 2020 | 97 | |
| 6 | 2019 | 70 | |
| 7 | 2013 | 68 | |
| 8 | 2021 | 62 | |
| 9 | 2012 | 35 | |
| 10 | 2021 | 33 | |
| 11 | 2019 | 29 | |
| 12 | 2020 | 28 | |
| 13 | 2019 | 24 | |
| 14 | 2020 | 22 | |
| 15 | 2021 | 21 | |
| 16 | 2022 | 20 | |
| 17 | 2022 | 20 | |
| 18 | 2022 | 18 | |
| 19 | 2019 | 14 | |
| 20 | 2020 | 13 |
About Dun Jack Fu
Dun Jack Fu is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Health Informatics and Cell Biology, having authored 45 papers that have together received 2.2k indexed citations. Recurring topics across this work include Retinal Diseases and Treatments (16 papers), Retinal Imaging and Analysis (7 papers), Glaucoma and retinal disorders (5 papers), Retinal and Optic Conditions (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Skin and Cellular Biology Research (3 papers), COVID-19 diagnosis using AI (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Health Informatics (496 citations), Ophthalmology (505 citations), Radiology, Nuclear Medicine and Imaging (829 citations), Health Information Management (105 citations) and Artificial Intelligence (409 citations). Dun Jack Fu has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Pearse A. Keane, Siegfried K. Wagner, Konstantinos Balaskas, Livia Faes, Alastair K. Denniston, Xiaoxuan Liu, Gabriella Moraes, Lucas M. Bachmann, Christoph Kern and Martin Schmid. Their work appears in journals such as British Journal of Ophthalmology, Eye, The Lancet Digital Health, BMJ Open Ophthalmology and Translational Vision Science & Technology.
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.