Charles Schmitt
- Biophysics top 2%
- Artificial Intelligence top 2%
- Health Informatics top 10%
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- Biomedical Text Mining and Ontologies 12
- Bioinformatics and Genomic Networks 4
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- Health, Environment, Cognitive Aging 10
- Air Quality and Health Impacts 5
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- Computational Drug Discovery Methods 7
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- Nutritional Studies and Diet 6
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- Scientific Computing and Data Management 5
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- Electronic Health Records Systems 5
- Co-authors
- David BorlandXiaojun GuanNancy E. ThomasJohn T. WoosleyJ. S. MarronMarc NiethammerChris BizonAlexander Tropsha
- Journals
- International Journal of Environmental Research and Public Health (3 papers)Clinical and Translational Science (2 papers)Nucleic Acids Research (2 papers)
- Partner nations
- United StatesCanadaBrazil
In The Last Decade
Charles Schmitt
48 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Biophysics 179
- Artificial Intelligence 648
- Computer Vision and Pattern Recognition 363
- Radiology, Nuclear Medicine and Imaging 342
- Health Informatics 19
Countries citing papers authored by Charles Schmitt
This map shows the geographic impact of Charles Schmitt'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 Charles Schmitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Charles Schmitt more than expected).
Fields of papers citing papers by Charles Schmitt
This network shows the impact of papers produced by Charles Schmitt. 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 Charles Schmitt. The network helps show where Charles Schmitt may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Charles Schmitt, 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 | 2024 | 1 | |
| 2 | 2024 | 7 | |
| 3 | 2023 | 5 | |
| 4 | 2023 | 3 | |
| 5 | 2023 | 2 | |
| 6 | 2023 | 7 | |
| 7 | 2022 | 18 | |
| 8 | 2022 | 8 | |
| 9 | 2021 | 7 | |
| 10 | 2021 | 18 | |
| 11 | 2021 | 15 | |
| 12 | 2020 | 27 | |
| 13 | Overview of the TAC 2018 Systematic Review Information Extraction Track. | 2018 | 4 |
| 14 | 2012 | 98 | |
| 15 | 2011 | 43 | |
| 16 | 2011 | 5 | |
| 17 | 2009 | 1 | |
| 18 | 2007 | 38 | |
| 19 | 2006 | 25 | |
| 20 | Interleukin-7 and malignant T cells. | 1993 | 3 |
About Charles Schmitt
Charles Schmitt is a scholar working on Health Information Management, Health, Toxicology and Mutagenesis and Information Systems and Management, having authored 53 papers that have together received 1.4k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (12 papers), Health, Environment, Cognitive Aging (10 papers), Computational Drug Discovery Methods (7 papers), Nutritional Studies and Diet (6 papers), Air Quality and Health Impacts (5 papers), Scientific Computing and Data Management (5 papers), Electronic Health Records Systems (5 papers) and Bioinformatics and Genomic Networks (4 papers). The work is most often cited by research in Biophysics (179 citations), Artificial Intelligence (648 citations) and Computer Vision and Pattern Recognition (363 citations). Charles Schmitt has collaborated with scholars based in United States, Canada and Brazil. Frequent co-authors include David Borland, Xiaojun Guan, Nancy E. Thomas, John T. Woosley, J. S. Marron, Marc Niethammer, Chris Bizon, Alexander Tropsha, Vinícius M. Alves and Eugene Muratov. Their work appears in journals such as International Journal of Environmental Research and Public Health, Clinical and Translational Science, Nucleic Acids Research, Journal of Exposure Science & Environmental Epidemiology and Environment International.
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.