Daniel Karlsson
- Molecular Biology
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience top 10%
- Health Information Management top 1%
- Computational Theory and Mathematics top 5%
- Co-authors
- Stefan ThorMagnus BaumgardtPetru ElesZebo PengJavier TerrienteFernando J. Díaz‐BenjumeaHans ÅhlfeldtMikael Nyström
- Topics
- Biomedical Text Mining and Ontologies (22 papers)Semantic Web and Ontologies (19 papers)Formal Methods in Verification (10 papers)
- Journals
- CellNature CommunicationsPLoS ONE
- Partner nations
- SwedenUnited StatesAustria
In The Last Decade
Daniel Karlsson
50 papers receiving 663 citations
Peers
Comparison fields: 5 of 102
- Molecular Biology 361
- Artificial Intelligence 146
- Cellular and Molecular Neuroscience 143
- Health Information Management 142
- Computational Theory and Mathematics 93
Countries citing papers authored by Daniel Karlsson
This map shows the geographic impact of Daniel Karlsson'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 Daniel Karlsson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Karlsson more than expected).
Fields of papers citing papers by Daniel Karlsson
This network shows the impact of papers produced by Daniel Karlsson. 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 Daniel Karlsson. The network helps show where Daniel Karlsson may publish in the future.
Co-authorship network of co-authors of Daniel Karlsson
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Karlsson. A scholar is included among the top collaborators of Daniel Karlsson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Karlsson. Daniel Karlsson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 11 | |
| 6 | A computable pathology report for precision medicine: extending an observables ontology unifying SNOMED CT and LOINC | 1 |
| 7 | 2 | |
| 8 | 57 | |
| 9 | 23 | |
| 10 | 16 | |
| 11 | Information Models and Ontologies for Representing the Electronic Health Record. | 3 |
| 12 | 134 | |
| 13 | 50 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 12 | |
| 17 | 3 | |
| 18 | A Formal Verification Approach for IP-based Designs | 1 |
| 19 | Digital pen technology in palliative home healthcare | 2 |
| 20 | 18 |
About Daniel Karlsson
Daniel Karlsson is a scholar working on Health Information Management, Software and Issues, ethics and legal aspects, having authored 54 papers that have together received 741 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (22 papers), Semantic Web and Ontologies (19 papers) and Formal Methods in Verification (10 papers). The work is most often cited by research in Health Information Management (142 citations), Hardware and Architecture (90 citations) and Issues, ethics and legal aspects (14 citations). Daniel Karlsson has collaborated with scholars based in Sweden, United States and Austria. Frequent co-authors include Stefan Thor, Magnus Baumgardt, Petru Eles, Zebo Peng, Javier Terriente, Fernando J. Díaz‐Benjumea, Hans Åhlfeldt, Mikael Nyström, Ryan B. MacDonald and Gunnar O. Klein. Their work appears in journals such as Cell, Nature Communications and PLoS ONE.
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.