Joy T. Wu
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
-
- Machine Learning in Healthcare 6
- AI in cancer detection 5
- Topic Modeling 4
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- COVID-19 diagnosis using AI 9
- Radiomics and Machine Learning in Medical Imaging 7
- Radiology practices and education 3
- Co-authors
- Leo Anthony Celi (4 shared papers)Tanveer Syeda-Mahmood (13 shared papers)Patrick D. Tyler (2 shared papers)Franck Dernoncourt (2 shared papers)Mehdi Moradi (9 shared papers)Sebastian Gehrmann (2 shared papers)Edward T. Moseley (2 shared papers)Eric T. Carlson (2 shared papers)
- Journals
- Journal of Digital Imaging (1 paper)Radiographics (1 paper)IEEE Transactions on Electron Devices (1 paper)PLoS ONE (1 paper)Radiology Artificial Intelligence (1 paper)
- Partner nations
- United StatesGermanyNew Zealand
In The Last Decade
Joy T. Wu
21 papers receiving 437 citations
Peers
Comparison fields: 5 of 100
- Health Informatics 77
- Health Information Management 43
- Radiology, Nuclear Medicine and Imaging 142
- Artificial Intelligence 172
- Family Practice 4
Countries citing papers authored by Joy T. Wu
This map shows the geographic impact of Joy T. Wu'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 Joy T. Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joy T. Wu more than expected).
Fields of papers citing papers by Joy T. Wu
This network shows the impact of papers produced by Joy T. Wu. 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 Joy T. Wu. The network helps show where Joy T. Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Joy T. Wu, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 149 | |
| 2 | 2020 | 94 | |
| 3 | 1976 | 44 | |
| 4 | 2017 | 26 | |
| 5 | 2019 | 23 | |
| 6 | 2020 | 21 | |
| 7 | 2010 | 15 | |
| 8 | 2020 | 14 | |
| 9 | 2021 | 13 | |
| 10 | 2023 | 10 | |
| 11 | 2019 | 10 | |
| 12 | 2022 | 9 | |
| 13 | 2020 | 9 | |
| 14 | AI Accelerated Human-in-the-loop Structuring of Radiology Reports. | 2020 | 8 |
| 15 | Combining Deep Learning and Knowledge-driven Reasoning for Chest X-Ray Findings Detection. | 2020 | 4 |
| 16 | Multimodal Pediatric Lymphoma Detection using PET and MRI. | 2023 | 4 |
| 17 | 2017 | 2 | |
| 18 | 2018 | 2 | |
| 19 | Semantic Expansion of Clinician Generated Data Preferences for Automatic Patient Data Summarization. | 2021 | 1 |
| 20 | 2019 | 1 |
About Joy T. Wu
Joy T. Wu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Molecular Biology, Health Informatics and Health Information Management, having authored 23 papers that have together received 460 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (9 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Machine Learning in Healthcare (6 papers), AI in cancer detection (5 papers), Topic Modeling (4 papers), Artificial Intelligence in Healthcare and Education (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Radiology practices and education (3 papers). The work is most often cited by research in Health Informatics (77 citations), Health Information Management (43 citations), Radiology, Nuclear Medicine and Imaging (142 citations), Artificial Intelligence (172 citations) and Family Practice (4 citations). Joy T. Wu has collaborated with scholars based in United States, Germany and New Zealand. Frequent co-authors include Leo Anthony Celi, Tanveer Syeda-Mahmood, Patrick D. Tyler, Franck Dernoncourt, Mehdi Moradi, Sebastian Gehrmann, Edward T. Moseley, Eric T. Carlson, Yeran Li and Jonathan Welt. Their work appears in journals such as Journal of Digital Imaging, Radiographics, IEEE Transactions on Electron Devices, PLoS ONE and Radiology Artificial Intelligence.
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.