Samuel Schäfer
Impact in
- Health Informatics top 2%
- Artificial Intelligence in Healthcare and Education
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- Digital Transformation in Industry
Papers in
-
- Single-cell and spatial transcriptomics 3
- Co-authors
- Mikael Benson (8 shared papers)Sandra Lilja (8 shared papers)Huan Zhang (6 shared papers)Xinxiu Li (6 shared papers)Danuta R. Gawel (5 shared papers)Oleg Sysoev (5 shared papers)Andreas Matussek (2 shared papers)Margaretha Stenmarker (2 shared papers)
- Journals
- Genome Medicine (3 papers)PLoS ONE (2 papers)Cytokine (1 paper)Scientific Reports (1 paper)Reproduction in Domestic Animals (1 paper)
- Partner nations
- SwedenSouth KoreaAustralia
In The Last Decade
Samuel Schäfer
14 papers receiving 380 citations
Peers
Comparison fields: 5 of 113
- Health Informatics 47
- Industrial and Manufacturing Engineering 104
- Biomedical Engineering 89
- Health Information Management 8
- Biophysics 9
Countries citing papers authored by Samuel Schäfer
This map shows the geographic impact of Samuel Schäfer'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 Samuel Schäfer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Schäfer more than expected).
Fields of papers citing papers by Samuel Schäfer
This network shows the impact of papers produced by Samuel Schäfer. 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 Samuel Schäfer. The network helps show where Samuel Schäfer may publish in the future.
Co-authors
The 25 scholars most cited alongside Samuel Schäfer, 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 | 2019 | 273 | |
| 2 | 2022 | 39 | |
| 3 | 2019 | 20 | |
| 4 | 2019 | 16 | |
| 5 | 2020 | 11 | |
| 6 | 2024 | 9 | |
| 7 | 2011 | 6 | |
| 8 | 2020 | 4 | |
| 9 | 2020 | 4 | |
| 10 | 2021 | 2 | |
| 11 | 2019 | 2 | |
| 12 | 2021 | 2 | |
| 13 | 1997 | 2 | |
| 14 | 2021 | 1 |
About Samuel Schäfer
Samuel Schäfer is a scholar working on Molecular Biology, Infectious Diseases, Otorhinolaryngology, Social Psychology and General Health Professions, having authored 14 papers that have together received 391 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (3 papers), Demographic Trends and Gender Preferences (1 paper), Pancreatic and Hepatic Oncology Research (1 paper), Sinusitis and nasal conditions (1 paper), Bioenergy crop production and management (1 paper), T-cell and B-cell Immunology (1 paper), Neuroendocrine regulation and behavior (1 paper) and Evolutionary Psychology and Human Behavior (1 paper). The work is most often cited by research in Health Informatics (47 citations), Industrial and Manufacturing Engineering (104 citations), Biomedical Engineering (89 citations), Health Information Management (8 citations) and Biophysics (9 citations). Samuel Schäfer has collaborated with scholars based in Sweden, South Korea and Australia. Frequent co-authors include Mikael Benson, Sandra Lilja, Huan Zhang, Xinxiu Li, Danuta R. Gawel, Oleg Sysoev, Andreas Matussek, Margaretha Stenmarker, Mika Gustafsson and Per Sandström. Their work appears in journals such as Genome Medicine, PLoS ONE, Cytokine, Scientific Reports and Reproduction in Domestic Animals.
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.