Kay Li
Impact in
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education
- Applied Psychology top 5%
- Digital Mental Health Interventions
Papers in
-
- Artificial Intelligence in Healthcare and Education 9
-
- AI in Service Interactions 7
- Machine Learning in Healthcare 3
- Co-authors
- James C. L. Chow (9 shared papers)Leslie Sanders (5 shared papers)Lu Xu (1 shared paper)Jiahua Li (1 shared paper)Hafiz Mudassir Munir (1 shared paper)Julie M. Paik (1 shared paper)Jianxiao Zou (1 shared paper)Chuan Xie (1 shared paper)
- Journals
- JMIR Cancer (2 papers)JMIR Formative Research (1 paper)Frontiers in Artificial Intelligence (1 paper)Clinical Diabetes (1 paper)Healthcare (1 paper)
- Partner nations
- CanadaUnited StatesChina
In The Last Decade
Kay Li
13 papers receiving 567 citations
Hit Papers
Peers
Comparison fields: 5 of 90
- Health Informatics 288
- Applied Psychology 98
- Artificial Intelligence 295
- Radiology, Nuclear Medicine and Imaging 156
- Health Information Management 30
Countries citing papers authored by Kay Li
This map shows the geographic impact of Kay Li'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 Kay Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kay Li more than expected).
Fields of papers citing papers by Kay Li
This network shows the impact of papers produced by Kay Li. 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 Kay Li. The network helps show where Kay Li may publish in the future.
Co-authors
The 11 scholars most cited alongside Kay Li, 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 | Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review Hit paper breakdown → | 2021 | 289 |
| 2 | 2023 | 111 | |
| 3 | 2024 | 38 | |
| 4 | 2023 | 35 | |
| 5 | 2024 | 33 | |
| 6 | 2023 | 30 | |
| 7 | 2022 | 20 | |
| 8 | 2025 | 13 | |
| 9 | 2019 | 8 | |
| 10 | 2025 | 7 | |
| 11 | 2021 | 3 | |
| 12 | 2005 | 2 | |
| 13 | 2016 | 1 | |
| 14 | 2016 | 1 | |
| 15 | 2024 | 0 | |
| 16 | A Country Bumpkin in Cosmopolitan Shanghai: John Woo's My Fair Gentleman and the Evolution of Pygmalion in Contemporary China | 2013 | 0 |
| 17 | 2013 | 0 | |
| 18 | 2021 | 0 |
About Kay Li
Kay Li is a scholar working on Health Informatics, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health and Surgery, having authored 18 papers that have together received 591 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (9 papers), AI in Service Interactions (7 papers), COVID-19 diagnosis using AI (5 papers), Machine Learning in Healthcare (3 papers), Literature Analysis and Criticism (2 papers), Pancreatic function and diabetes (1 paper), Multilevel Inverters and Converters (1 paper) and Diabetes Management and Research (1 paper). The work is most often cited by research in Health Informatics (288 citations), Applied Psychology (98 citations), Artificial Intelligence (295 citations), Radiology, Nuclear Medicine and Imaging (156 citations) and Health Information Management (30 citations). Kay Li has collaborated with scholars based in Canada, United States and China. Frequent co-authors include James C. L. Chow, Leslie Sanders, Lu Xu, Jiahua Li, Hafiz Mudassir Munir, Julie M. Paik, Jianxiao Zou, Chuan Xie, Josep M. Guerrero and Talha Younas. Their work appears in journals such as JMIR Cancer, JMIR Formative Research, Frontiers in Artificial Intelligence, Clinical Diabetes and Healthcare.
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.