David C. Seong
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
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- Immunotherapy and Immune Responses
- Immune cells in cancer
- T-cell and B-cell Immunology
Papers in
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- Artificial Intelligence in Healthcare and Education 1
-
- Immune cells in cancer 1
- Immunotherapy and Immune Responses 1
- Co-authors
- Juliana Idoyaga (3 shared papers)Andres Gottfried‐Blackmore (3 shared papers)Hayley M. Raquer-McKay (2 shared papers)Rebeca Arroyo Hornero (2 shared papers)Nicholas M. Adams (1 shared paper)Boris Reizis (1 shared paper)Adeeb H Rahman (1 shared paper)Tae Jin Yun (1 shared paper)
- Journals
- Science Immunology (1 paper)Parkinsonism & Related Disorders (1 paper)Nature Immunology (1 paper)Nature Medicine (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesGermanyFrance
In The Last Decade
David C. Seong
13 papers receiving 174 citations
David C. Seong's Hit Papers
Peers
Comparison fields: 5 of 29
- Health Informatics 16
- Immunology 63
- Nutrition and Dietetics 7
- Oncology 8
- Health Information Management 2
Countries citing papers authored by David C. Seong
This map shows the geographic impact of David C. Seong'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 David C. Seong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David C. Seong more than expected).
Fields of papers citing papers by David C. Seong
This network shows the impact of papers produced by David C. Seong. 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 David C. Seong. The network helps show where David C. Seong may publish in the future.
Co-authors
The 25 scholars most cited alongside David C. Seong, 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 | 2023 | 68 | |
| 2 | A machine learning approach to leveraging electronic health records for enhanced omics analysis Hit paper breakdown → | 2025 | 29 |
| 3 | 2023 | 27 | |
| 4 | 2025 | 13 | |
| 5 | 2025 | 10 | |
| 6 | 2019 | 7 | |
| 7 | 2025 | 5 | |
| 8 | 2025 | 5 | |
| 9 | 2024 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2025 | 2 | |
| 12 | 2025 | 2 | |
| 13 | 2024 | 1 | |
| 14 | 2025 | 0 |
About David C. Seong
David C. Seong is a scholar working on Health Informatics, Immunology, Artificial Intelligence, Statistics, Probability and Uncertainty and Cellular and Molecular Neuroscience, having authored 14 papers that have together received 177 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (3 papers), Single-cell and spatial transcriptomics (2 papers), Artificial Intelligence in Healthcare and Education (1 paper), Immune cells in cancer (1 paper), Immunotherapy and Immune Responses (1 paper), Parkinson's Disease Mechanisms and Treatments (1 paper), Genetic Neurodegenerative Diseases (1 paper) and scientometrics and bibliometrics research (1 paper). The work is most often cited by research in Health Informatics (16 citations), Immunology (63 citations), Nutrition and Dietetics (7 citations), Oncology (8 citations) and Health Information Management (2 citations). David C. Seong has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Juliana Idoyaga, Andres Gottfried‐Blackmore, Hayley M. Raquer-McKay, Rebeca Arroyo Hornero, Nicholas M. Adams, Boris Reizis, Adeeb H Rahman, Tae Jin Yun, Marcela Alcántara‐Hernández and Oriana A. Perez. Their work appears in journals such as Science Immunology, Parkinsonism & Related Disorders, Nature Immunology, Nature Medicine and Nature Communications.
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.