Simon Meyer Lauritsen
- Artificial Intelligence top 5%
- Epidemiology
- Health Informatics top 2%
- Health Information Management top 5%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Marianne Johansson JørgensenBo ThiessonJeppe LangeKatrine Meyer LauritsenMathias Vassard OlsenMads Ruben Burgdorff KristensenAnders H. RiisUlrick Espelund
- Topics
- Machine Learning in Healthcare (4 papers)Sepsis Diagnosis and Treatment (3 papers)Healthcare Policy and Management (2 papers)
- Partner nations
- DenmarkUnited KingdomUnited States
In The Last Decade
Simon Meyer Lauritsen
7 papers receiving 406 citations
Hit Papers
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 251
- Epidemiology 132
- Health Informatics 82
- Health Information Management 59
- Radiology, Nuclear Medicine and Imaging 48
Countries citing papers authored by Simon Meyer Lauritsen
This map shows the geographic impact of Simon Meyer Lauritsen'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 Simon Meyer Lauritsen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon Meyer Lauritsen more than expected).
Fields of papers citing papers by Simon Meyer Lauritsen
This network shows the impact of papers produced by Simon Meyer Lauritsen. 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 Simon Meyer Lauritsen. The network helps show where Simon Meyer Lauritsen may publish in the future.
Co-authorship network of co-authors of Simon Meyer Lauritsen
This figure shows the co-authorship network connecting the top 25 collaborators of Simon Meyer Lauritsen. A scholar is included among the top collaborators of Simon Meyer Lauritsen 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 Simon Meyer Lauritsen. Simon Meyer Lauritsen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 36 | |
| 4 | 106 | |
| 5 | 10 | |
| 6 | Explainable artificial intelligence model to predict acute critical illness from electronic health recordsbreakdown → | 257 |
| 7 | 3 |
About Simon Meyer Lauritsen
Simon Meyer Lauritsen is a scholar working on Health Informatics, Family Practice and Health Information Management, having authored 7 papers that have together received 418 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (4 papers), Sepsis Diagnosis and Treatment (3 papers) and Healthcare Policy and Management (2 papers). The work is most often cited by research in Health Informatics (82 citations), Family Practice (35 citations) and Health Information Management (59 citations). Simon Meyer Lauritsen has collaborated with scholars based in Denmark, United Kingdom and United States. Frequent co-authors include Marianne Johansson Jørgensen, Bo Thiesson, Jeppe Lange, Katrine Meyer Lauritsen, Mathias Vassard Olsen, Mads Ruben Burgdorff Kristensen, Anders H. Riis, Ulrick Espelund, Jesper Weile and Pia Kjær Kristensen. Their work appears in journals such as Nature Communications, Medical Care and BMJ Open.
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.