Spencer A. Thomas
- Health Informatics top 5%
- Microbiology top 10%
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- Genetic Syndromes and Imprinting 3
- Artificial Intelligence top 10%
- AI in cancer detection 9
- Machine Learning in Healthcare 5
- Health Information Management top 10%
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- Metabolomics and Mass Spectrometry Studies 4
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- Digital Imaging for Blood Diseases 4
- Generative Adversarial Networks and Image Synthesis 3
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- Oral and Maxillofacial Pathology 4
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- Radiomics and Machine Learning in Medical Imaging 4
- Co-authors
- Yaochu JinPeter C. HarrisJosephine BunchIan S. GilmoreCarlos López‐LarreaPeter J. RatcliffeM.H. BreuningEliécer Coto
- Journals
- The Lancet (1 paper)SHILAP Revista de lepidopterología (3 papers)Analytical Chemistry (1 paper)
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
Spencer A. Thomas
45 papers receiving 619 citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Health Informatics 48
- Microbiology 48
- Genetics 138
- Artificial Intelligence 152
- Health Information Management 22
Countries citing papers authored by Spencer A. Thomas
This map shows the geographic impact of Spencer A. Thomas'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 Spencer A. Thomas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Spencer A. Thomas more than expected).
Fields of papers citing papers by Spencer A. Thomas
This network shows the impact of papers produced by Spencer A. Thomas. 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 Spencer A. Thomas. The network helps show where Spencer A. Thomas may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Spencer A. Thomas, 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 | 0 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 1 | |
| 7 | 2024 | 9 | |
| 8 | Large language models to identify social determinants of health in electronic health recordsbreakdown → | 2024 | 119 |
| 9 | 2024 | 1 | |
| 10 | 2024 | 1 | |
| 11 | 2023 | 0 | |
| 12 | 2023 | 2 | |
| 13 | 2023 | 1 | |
| 14 | 2022 | 8 | |
| 15 | 2022 | 10 | |
| 16 | 2020 | 2 | |
| 17 | Analysis of Primary Care Computerised Medical Records with Deep Learning. | 2019 | 3 |
| 18 | Analyzing regime shifts in agent-based models with equation-free analysis | 2016 | 2 |
| 19 | 2006 | 1 | |
| 20 | 2006 | 54 |
About Spencer A. Thomas
Spencer A. Thomas is a scholar working on Health Informatics, Transplantation and Oral Surgery, having authored 52 papers that have together received 638 indexed citations. Recurring topics across this work include AI in cancer detection (9 papers), Machine Learning in Healthcare (5 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Digital Imaging for Blood Diseases (4 papers), Oral and Maxillofacial Pathology (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Genetic Syndromes and Imprinting (3 papers) and Generative Adversarial Networks and Image Synthesis (3 papers). The work is most often cited by research in Health Informatics (48 citations), Microbiology (48 citations) and Genetics (138 citations). Spencer A. Thomas has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Yaochu Jin, Peter C. Harris, Josephine Bunch, Ian S. Gilmore, Carlos López‐Larrea, Peter J. Ratcliffe, M.H. Breuning, Eliécer Coto, Rory T. Steven and Paul J. Catalano. Their work appears in journals such as The Lancet, SHILAP Revista de lepidopterología and Analytical Chemistry.
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.