Claire Cui
Impact in
- Health Informatics top 0.05%
- Artificial Intelligence in Healthcare and Education
- Health Information Management top 0.5%
- Artificial Intelligence in Healthcare
Papers in
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- Machine Learning in Healthcare 3
- Data Stream Mining Techniques 1
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- Efficiency Analysis Using DEA 3
- Co-authors
- Katherine Chou (2 shared papers)Sebastian Thrun (1 shared paper)Greg S. Corrado (1 shared paper)Andre Esteva (1 shared paper)Jeff Dean (1 shared paper)Volodymyr Kuleshov (1 shared paper)Bharath Ramsundar (1 shared paper)Mark A. DePristo (1 shared paper)
- Journals
- Nature Medicine (1 paper)Meditari Accountancy Research (1 paper)Journal of Revenue and Pricing Management (1 paper)Clinical Pharmacology & Therapeutics (1 paper)Annals of Operations Research (1 paper)
- Partner nations
- United StatesNew Zealand
In The Last Decade
Claire Cui
8 papers receiving 2.3k citations
Claire Cui's Hit Papers
Peers
Comparison fields: 5 of 169
- Health Informatics 665
- Health Information Management 304
- Radiology, Nuclear Medicine and Imaging 742
- Artificial Intelligence 921
- Family Practice 37
Countries citing papers authored by Claire Cui
This map shows the geographic impact of Claire Cui'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 Claire Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Claire Cui more than expected).
Fields of papers citing papers by Claire Cui
This network shows the impact of papers produced by Claire Cui. 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 Claire Cui. The network helps show where Claire Cui may publish in the future.
Co-authors
The 25 scholars most cited alongside Claire Cui, 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 | A guide to deep learning in healthcare Hit paper breakdown → | 2018 | 2350 |
| 2 | 2019 | 36 | |
| 3 | 2020 | 16 | |
| 4 | 2021 | 4 | |
| 5 | 2020 | 3 | |
| 6 | 2025 | 1 | |
| 7 | 2017 | 1 | |
| 8 | 2024 | 1 | |
| 9 | 2025 | 0 |
About Claire Cui
Claire Cui is a scholar working on Artificial Intelligence, Management Science and Operations Research, Health Information Management, Economics and Econometrics and Management Information Systems, having authored 9 papers that have together received 2.4k indexed citations. Recurring topics across this work include Efficiency Analysis Using DEA (3 papers), Machine Learning in Healthcare (3 papers), Data Stream Mining Techniques (1 paper), Pharmaceutical Practices and Patient Outcomes (1 paper), COVID-19 diagnosis using AI (1 paper), Ophthalmology and Visual Health Research (1 paper), Artificial Intelligence in Healthcare (1 paper) and Monetary Policy and Economic Impact (1 paper). The work is most often cited by research in Health Informatics (665 citations), Health Information Management (304 citations), Radiology, Nuclear Medicine and Imaging (742 citations), Artificial Intelligence (921 citations) and Family Practice (37 citations). Claire Cui has collaborated with scholars based in United States and New Zealand. Frequent co-authors include Katherine Chou, Sebastian Thrun, Greg S. Corrado, Andre Esteva, Jeff Dean, Volodymyr Kuleshov, Bharath Ramsundar, Mark A. DePristo, Alvin Rajkomar and Laura Vardoulakis. Their work appears in journals such as Nature Medicine, Meditari Accountancy Research, Journal of Revenue and Pricing Management, Clinical Pharmacology & Therapeutics and Annals of Operations Research.
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.