Kengo Miyo
- Infectious Diseases
- Artificial Intelligence
- Clinical Psychology
- General Health Professions
- Epidemiology
- Co-authors
- Kazuhiko OheEiji AramakiTakeshi ImaiNorio OhmagariMaki KonishiShohei YamamotoTetsuya MizoueAkihito Tanaka
- Topics
- Biomedical Text Mining and Ontologies (6 papers)COVID-19 and Mental Health (6 papers)SARS-CoV-2 and COVID-19 Research (5 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Kengo Miyo
25 papers receiving 184 citations
Peers
Comparison fields: 5 of 63
- Infectious Diseases 53
- Artificial Intelligence 36
- Clinical Psychology 31
- General Health Professions 30
- Epidemiology 26
Countries citing papers authored by Kengo Miyo
This map shows the geographic impact of Kengo Miyo'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 Kengo Miyo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kengo Miyo more than expected).
Fields of papers citing papers by Kengo Miyo
This network shows the impact of papers produced by Kengo Miyo. 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 Kengo Miyo. The network helps show where Kengo Miyo may publish in the future.
Co-authorship network of co-authors of Kengo Miyo
This figure shows the co-authorship network connecting the top 25 collaborators of Kengo Miyo. A scholar is included among the top collaborators of Kengo Miyo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kengo Miyo. Kengo Miyo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 13 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 39 | |
| 7 | 1 | |
| 8 | 17 | |
| 9 | 10 | |
| 10 | 4 | |
| 11 | 1 | |
| 12 | 26 | |
| 13 | 9 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | Orthographic Disambiguation Incorporating Transliterated Probability. | 16 |
| 17 | Support vector machine based orthographic disambiguation. | 4 |
| 18 | Development of case-based medication alerting and recommender system: a new approach to prevention for medication error. | 7 |
| 19 | Statistical selector of the best multiple ICD-coding method. | 2 |
| 20 | Toward Medical Ontology using Natural Language Processing. | 2 |
About Kengo Miyo
Kengo Miyo is a scholar working on Health Information Management, Medical Laboratory Technology and Geriatrics and Gerontology, having authored 27 papers that have together received 193 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (6 papers), COVID-19 and Mental Health (6 papers) and SARS-CoV-2 and COVID-19 Research (5 papers). The work is most often cited by research in Health Information Management (22 citations), Health Informatics (4 citations) and Infectious Diseases (53 citations). Kengo Miyo has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Kazuhiko Ohe, Eiji Aramaki, Takeshi Imai, Norio Ohmagari, Maki Konishi, Shohei Yamamoto, Tetsuya Mizoue, Akihito Tanaka, Wataru Sugiura and Haruhito Sugiyama. Their work appears in journals such as PLoS ONE, IEEE Transactions on Medical Imaging and Vaccine.
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.