Scott L. Fleming
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
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- Artificial Intelligence in Healthcare
Papers in
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- Artificial Intelligence in Healthcare and Education 4
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- Electronic Health Records Systems 3
- Co-authors
- Nigam H. ShahJason FriesEthan SteinbergJose PosadaLeanne M. WilliamsMichael A. PfefferYizhe XuBirju Patel
- Journals
- npj Digital Medicine (3 papers)Applied Clinical Informatics (2 papers)Radiology Artificial Intelligence (1 paper)Scientific Reports (1 paper)Biological Psychiatry (1 paper)
- Partner nations
- United StatesCanadaColombia
In The Last Decade
Scott L. Fleming
25 papers receiving 717 citations
Peers
Comparison fields: 5 of 111
- Health Informatics 154
- Health Information Management 80
- Cognitive Neuroscience 161
- Artificial Intelligence 251
- Experimental and Cognitive Psychology 82
Countries citing papers authored by Scott L. Fleming
This map shows the geographic impact of Scott L. Fleming'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 Scott L. Fleming with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scott L. Fleming more than expected).
Fields of papers citing papers by Scott L. Fleming
This network shows the impact of papers produced by Scott L. Fleming. 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 Scott L. Fleming. The network helps show where Scott L. Fleming may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Scott L. Fleming, 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 | 2024 | 9 | |
| 3 | 2024 | 2 | |
| 4 | 2023 | 143 | |
| 5 | 2023 | 28 | |
| 6 | 2023 | 26 | |
| 7 | 2022 | 5 | |
| 8 | 2022 | 11 | |
| 9 | 2022 | 8 | |
| 10 | 2022 | 3 | |
| 11 | 2021 | 4 | |
| 12 | 2021 | 45 | |
| 13 | Reinforcement Learning with State Observation Costs in Action-Contingent Noiselessly Observable Markov Decision Processes | 2021 | 4 |
| 14 | 2021 | 82 | |
| 15 | 2020 | 33 | |
| 16 | 2020 | 113 | |
| 17 | 2020 | 38 | |
| 18 | 2020 | 19 | |
| 19 | 2020 | 3 | |
| 20 | 2019 | 62 |
About Scott L. Fleming
Scott L. Fleming is a scholar working on Health Informatics, Health Information Management, Artificial Intelligence, Applied Psychology and Cognitive Neuroscience, having authored 27 papers that have together received 734 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (9 papers), Functional Brain Connectivity Studies (5 papers), Artificial Intelligence in Healthcare and Education (4 papers), Sepsis Diagnosis and Treatment (4 papers), Electronic Health Records Systems (3 papers), Mental Health Research Topics (3 papers), Biomedical Text Mining and Ontologies (2 papers) and Topic Modeling (2 papers). The work is most often cited by research in Health Informatics (154 citations), Health Information Management (80 citations), Cognitive Neuroscience (161 citations), Artificial Intelligence (251 citations) and Experimental and Cognitive Psychology (82 citations). Scott L. Fleming has collaborated with scholars based in United States, Canada and Colombia. Frequent co-authors include Nigam H. Shah, Jason Fries, Ethan Steinberg, Jose Posada, Leanne M. Williams, Michael A. Pfeffer, Yizhe Xu, Birju Patel, Michael Wornow and Rahul Thapa. Their work appears in journals such as npj Digital Medicine, Applied Clinical Informatics, Radiology Artificial Intelligence, Scientific Reports and Biological Psychiatry.
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.