Bo Thiesson
- Artificial Intelligence top 5%
- Epidemiology
- Health Informatics top 2%
- Signal Processing top 10%
- Information Systems top 10%
- Co-authors
- Marianne Johansson JørgensenSimon Meyer LauritsenJeppe LangeKatrine Meyer LauritsenDavid HeckermanChristopher MeekMathias Vassard OlsenMads Ruben Burgdorff Kristensen
- Topics
- Bayesian Modeling and Causal Inference (7 papers)Bayesian Methods and Mixture Models (5 papers)Algorithms and Data Compression (5 papers)
- Partner nations
- DenmarkUnited StatesUnited Kingdom
In The Last Decade
Bo Thiesson
36 papers receiving 696 citations
Hit Papers
Peers
Comparison fields: 5 of 133
- Artificial Intelligence 458
- Epidemiology 136
- Health Informatics 81
- Signal Processing 68
- Information Systems 65
Countries citing papers authored by Bo Thiesson
This map shows the geographic impact of Bo Thiesson'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 Bo Thiesson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Thiesson more than expected).
Fields of papers citing papers by Bo Thiesson
This network shows the impact of papers produced by Bo Thiesson. 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 Bo Thiesson. The network helps show where Bo Thiesson may publish in the future.
Co-authorship network of co-authors of Bo Thiesson
This figure shows the co-authorship network connecting the top 25 collaborators of Bo Thiesson. A scholar is included among the top collaborators of Bo Thiesson 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 Bo Thiesson. Bo Thiesson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 7 | |
| 4 | 9 | |
| 5 | 36 | |
| 6 | 106 | |
| 7 | Explainable artificial intelligence model to predict acute critical illness from electronic health recordsbreakdown → | 257 |
| 8 | 1 | |
| 9 | Analyzing Social Media Relationships in Context with Discussion Graphs | 1 |
| 10 | Fast Variational Mode-Seeking | 4 |
| 11 | Fast Large-scale Mixture Modeling with Component-specific Data Partitions | 1 |
| 12 | Markov Topic Models | 26 |
| 13 | 3 | |
| 14 | Asymmetric gradient boosting with application to spam filtering | 15 |
| 15 | Efficient Gradient Computation for Conditional Gaussian Models. | 0 |
| 16 | 8 | |
| 17 | Discriminative Model Selection for Density Models. | 4 |
| 18 | The Learning Curve Method Applied to Clustering | 2 |
| 19 | Learning Mixtures of Bayesian Networks | 18 |
| 20 | Accelerated quantification of Bayesian networks with incomplete data | 39 |
About Bo Thiesson
Bo Thiesson is a scholar working on Artificial Intelligence, Signal Processing and Family Practice, having authored 38 papers that have together received 726 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (7 papers), Bayesian Methods and Mixture Models (5 papers) and Algorithms and Data Compression (5 papers). The work is most often cited by research in Health Informatics (81 citations), Family Practice (32 citations) and Artificial Intelligence (458 citations). Bo Thiesson has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include Marianne Johansson Jørgensen, Simon Meyer Lauritsen, Jeppe Lange, Katrine Meyer Lauritsen, David Heckerman, Christopher Meek, Mathias Vassard Olsen, Mads Ruben Burgdorff Kristensen, Søren Højsgaard and Kenneth Church. Their work appears in journals such as Nature Communications, Medical Care and Machine Learning.
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.