Ming Tai‐Seale
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- General Health Professions top 2%
- Patient-Provider Communication in Healthcare
- Patient Satisfaction in Healthcare
- Primary Care and Health Outcomes
Papers in
-
- Artificial Intelligence in Healthcare and Education 4
- Co-authors
- Gerard J. WedigCheryl D. StultsMarlynn L. MayBita A. KashChris LonghurstRachel BramsonDorothy Y. HungMarcia G. Ory
- Journals
- Health Affairs (4 papers)Journal of Ambulatory Care Management (4 papers)Clinical Medicine & Research (3 papers)Medical Care Research and Review (3 papers)JMIR mhealth and uhealth (2 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Ming Tai‐Seale
55 papers receiving 863 citations
Peers
Comparison fields: 5 of 107
- Health Informatics 46
- General Health Professions 507
- Family Practice 27
- Geriatrics and Gerontology 47
- Health Information Management 54
Countries citing papers authored by Ming Tai‐Seale
This map shows the geographic impact of Ming Tai‐Seale'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 Ming Tai‐Seale with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Tai‐Seale more than expected).
Fields of papers citing papers by Ming Tai‐Seale
This network shows the impact of papers produced by Ming Tai‐Seale. 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 Ming Tai‐Seale. The network helps show where Ming Tai‐Seale may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Tai‐Seale, 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 | 2025 | 4 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2024 | 17 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 9 | |
| 9 | 2023 | 26 | |
| 10 | 2023 | 19 | |
| 11 | 2022 | 2 | |
| 12 | 2022 | 8 | |
| 13 | 2021 | 15 | |
| 14 | 2021 | 10 | |
| 15 | 2020 | 27 | |
| 16 | 2020 | 6 | |
| 17 | 2020 | 1 | |
| 18 | 2019 | 5 | |
| 19 | 2019 | 4 | |
| 20 | 2002 | 80 |
About Ming Tai‐Seale
Ming Tai‐Seale is a scholar working on Health Informatics, Family Practice, General Health Professions, Applied Psychology and Geriatrics and Gerontology, having authored 58 papers that have together received 917 indexed citations. Recurring topics across this work include Healthcare Policy and Management (14 papers), Primary Care and Health Outcomes (13 papers), Patient Satisfaction in Healthcare (13 papers), Patient-Provider Communication in Healthcare (11 papers), Healthcare Systems and Technology (5 papers), Mobile Health and mHealth Applications (4 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers) and Artificial Intelligence in Healthcare and Education (4 papers). The work is most often cited by research in Health Informatics (46 citations), General Health Professions (507 citations), Family Practice (27 citations), Geriatrics and Gerontology (47 citations) and Health Information Management (54 citations). Ming Tai‐Seale has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Gerard J. Wedig, Cheryl D. Stults, Marlynn L. May, Bita A. Kash, Chris Longhurst, Rachel Bramson, Dorothy Y. Hung, Marcia G. Ory, Robert L. Obenchain and Thomas W. Croghan. Their work appears in journals such as Health Affairs, Journal of Ambulatory Care Management, Clinical Medicine & Research, Medical Care Research and Review and JMIR mhealth and uhealth.
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.