Haiwen Gui
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
Papers in
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- AI in cancer detection 2
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- Bacterial biofilms and quorum sensing 2
- Co-authors
- Jesutofunmi A. Omiye (3 shared papers)Roxana Daneshjou (6 shared papers)James Zou (1 shared paper)Shawheen J. Rezaei (1 shared paper)Zhuo Ran Cai (1 shared paper)Vijaytha Muralidharan (1 shared paper)Crystal Chang (1 shared paper)Sophia Y. Wang (2 shared papers)
- Journals
- Journal of Investigative Dermatology (2 papers)JAMA Dermatology (2 papers)eLife (1 paper)Annals of Internal Medicine (1 paper)International Journal of Medical Informatics (1 paper)
- Partner nations
- United States
In The Last Decade
Haiwen Gui
11 papers receiving 243 citations
Haiwen Gui's Hit Papers
Peers
Comparison fields: 5 of 72
- Health Informatics 81
- Family Practice 4
- Health Information Management 8
- Artificial Intelligence 54
- Dermatology 13
Countries citing papers authored by Haiwen Gui
This map shows the geographic impact of Haiwen Gui'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 Haiwen Gui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haiwen Gui more than expected).
Fields of papers citing papers by Haiwen Gui
This network shows the impact of papers produced by Haiwen Gui. 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 Haiwen Gui. The network helps show where Haiwen Gui may publish in the future.
Co-authors
The 25 scholars most cited alongside Haiwen Gui, 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 | Large Language Models in Medicine: The Potentials and Pitfalls Hit paper breakdown → | 2024 | 159 |
| 2 | 2023 | 33 | |
| 3 | 2021 | 13 | |
| 4 | 2024 | 11 | |
| 5 | 2022 | 10 | |
| 6 | 2021 | 9 | |
| 7 | 2022 | 5 | |
| 8 | 2022 | 2 | |
| 9 | 2023 | 2 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2025 | 0 | |
| 13 | 2024 | 0 |
About Haiwen Gui
Haiwen Gui is a scholar working on Artificial Intelligence, Molecular Biology, Dermatology, Oncology and Health Informatics, having authored 13 papers that have together received 246 indexed citations. Recurring topics across this work include Cutaneous Melanoma Detection and Management (2 papers), Bacterial biofilms and quorum sensing (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), AI in cancer detection (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), Coagulation, Bradykinin, Polyphosphates, and Angioedema (1 paper), Contact Dermatitis and Allergies (1 paper) and Allergic Rhinitis and Sensitization (1 paper). The work is most often cited by research in Health Informatics (81 citations), Family Practice (4 citations), Health Information Management (8 citations), Artificial Intelligence (54 citations) and Dermatology (13 citations). Haiwen Gui has collaborated with scholars based in United States. Frequent co-authors include Jesutofunmi A. Omiye, Roxana Daneshjou, James Zou, Shawheen J. Rezaei, Zhuo Ran Cai, Vijaytha Muralidharan, Crystal Chang, Sophia Y. Wang, Lisa Willis and Heidi A. Arjes. Their work appears in journals such as Journal of Investigative Dermatology, JAMA Dermatology, eLife, Annals of Internal Medicine and International Journal of Medical Informatics.
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.