Citations per year, relative to Henrik Boström Henrik Boström (= 1×)
peers
Jianying Hu
Countries citing papers authored by Henrik Boström
Since
Specialization
Citations
This map shows the geographic impact of Henrik Boström'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 Henrik Boström with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Henrik Boström more than expected).
This network shows the impact of papers produced by Henrik Boström. 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 Henrik Boström. The network helps show where Henrik Boström may publish in the future.
Co-authorship network of co-authors of Henrik Boström
This figure shows the co-authorship network connecting the top 25 collaborators of Henrik Boström.
A scholar is included among the top collaborators of Henrik Boström 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 Henrik Boström. Henrik Boström is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Boström, Henrik, et al.. (2016). Learning Decision Trees from Histogram Data Using Multiple Subsets of Bins. The Florida AI Research Society. 430–435.6 indexed citations
5.
Zhao, Jing, Isak Karlsson, Lars Asker, & Henrik Boström. (2013). Applying Methods for Signal Detection in Spontaneous Reports to Electronic Patient Records. Knowledge Discovery and Data Mining.4 indexed citations
Boström, Henrik & Hercules Dalianis. (2012). De-identifying health records by means of active learning. International Conference on Machine Learning.11 indexed citations
8.
Johansson, Ulf, et al.. (2011). The Trade-Off between Accuracy and Interpretability for Predictive In Silico Modeling. Future Medicinal Chemistry. 3.1 indexed citations
9.
Boström, Henrik, et al.. (2009). Fusion of dimensionality reduction methods: A case study in microarray classification. KTH Publication Database DiVA (KTH Royal Institute of Technology). 460–465.5 indexed citations
10.
Johansson, Ulf, Henrik Boström, & Rikard König. (2008). Extending Nearest Neighbor Classification with Spheres of Confidence. KTH Publication Database DiVA (KTH Royal Institute of Technology). 282–287.6 indexed citations
Boström, Henrik, et al.. (2007). Using background knowledge for graph based learning : a case study in chemoinformatics. KTH Publication Database DiVA (KTH Royal Institute of Technology). 153–157.2 indexed citations
13.
Boström, Henrik, et al.. (2007). Classification with Intersecting rules.
14.
Boström, Henrik, et al.. (2006). Learning to Classify Structured Data by Graph Propositionalization. KTH Publication Database DiVA (KTH Royal Institute of Technology). 283–288.4 indexed citations
15.
Boström, Henrik. (2005). Maximizing the Area under the ROC Curve using Incremental Reduced Error Pruning. International Conference on Machine Learning. 346 Pt 2. 313–20.11 indexed citations
16.
Boström, Henrik. (2004). Pruning and Exclusion Criteria for Unordered Incremental Reduced Error Pruning. KTH Publication Database DiVA (KTH Royal Institute of Technology).6 indexed citations
17.
Boström, Henrik. (1996). Theory-Guideed Induction of Logic Programs by Inference of Regular Languages.. International Conference on Machine Learning. 46–53.7 indexed citations
18.
Gyimóthy, Tibor, et al.. (1996). Integrating Algorithmic Debugging and Unfolding Transformation in an Interactive Learner. European Conference on Artificial Intelligence. 403–407.4 indexed citations
Boström, Henrik. (1959). Cystinuria in Sweden. III. The prognosis of homozygous cystinuria.. PubMed. 116(4). 287–95.6 indexed citations
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.