Emma Chen
Impact in
- Health Informatics top 0.1%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Artificial Intelligence in Healthcare and Education 7
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- Multimodal Machine Learning Applications 2
- Digital Imaging for Blood Diseases 1
- Co-authors
- Pranav Rajpurkar (8 shared papers)Eric J. Topol (2 shared papers)Oishi Banerjee (1 shared paper)David A. Kim (3 shared papers)Vijay Janapa Reddi (2 shared papers)Tingying Helen Zeng (2 shared papers)Agustina D. Saenz (1 shared paper)Henrik Marklund (1 shared paper)
- Journals
- Cell (1 paper)Nature Medicine (1 paper)Journal of Biomedical Informatics (1 paper)Nature Biomedical Engineering (1 paper)The Lancet Digital Health (1 paper)
- Partner nations
- United States
In The Last Decade
Emma Chen
10 papers receiving 1.9k citations
Emma Chen's Hit Papers
Peers
Comparison fields: 5 of 145
- Health Informatics 916
- Health Information Management 153
- Artificial Intelligence 368
- Safety Research 107
- Radiology, Nuclear Medicine and Imaging 119
Countries citing papers authored by Emma Chen
This map shows the geographic impact of Emma Chen'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 Emma Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emma Chen more than expected).
Fields of papers citing papers by Emma Chen
This network shows the impact of papers produced by Emma Chen. 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 Emma Chen. The network helps show where Emma Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Emma Chen, 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 | AI in health and medicine Hit paper breakdown → | 2022 | 1788 |
| 2 | The generative era of medical AI Hit paper breakdown → | 2025 | 52 |
| 3 | 2023 | 33 | |
| 4 | 2023 | 20 | |
| 5 | 2022 | 17 | |
| 6 | 2021 | 13 | |
| 7 | 2023 | 3 | |
| 8 | 2025 | 3 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2025 | 0 | |
| 12 | 2026 | 0 | |
| 13 | 2026 | 0 |
About Emma Chen
Emma Chen is a scholar working on Health Informatics, Computer Vision and Pattern Recognition, Periodontics, Anesthesiology and Pain Medicine and Hardware and Architecture, having authored 13 papers that have together received 1.9k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (7 papers), Multimodal Machine Learning Applications (2 papers), Machine Learning in Healthcare (2 papers), Embedded Systems Design Techniques (1 paper), Energy Efficiency in Computing (1 paper), Tracheal and airway disorders (1 paper), Dementia and Cognitive Impairment Research (1 paper) and Digital Imaging for Blood Diseases (1 paper). The work is most often cited by research in Health Informatics (916 citations), Health Information Management (153 citations), Artificial Intelligence (368 citations), Safety Research (107 citations) and Radiology, Nuclear Medicine and Imaging (119 citations). Emma Chen has collaborated with scholars based in United States. Frequent co-authors include Pranav Rajpurkar, Eric J. Topol, Oishi Banerjee, David A. Kim, Vijay Janapa Reddi, Tingying Helen Zeng, Agustina D. Saenz, Henrik Marklund, Mikhail Y. Shalaginov and A.Y. Ng. Their work appears in journals such as Cell, Nature Medicine, Journal of Biomedical Informatics, Nature Biomedical Engineering and The Lancet Digital Health.
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.