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2020 – today
- 2024
[j6]Alfred Ultsch, Jörn Lötsch:
Augmenting small biomedical datasets using generative AI methods based on self-organizing neural networks. Briefings Bioinform. 26(1) (2024)- 2022
- [j5]Alfred Ultsch, Jörn Lötsch
:
Euclidean distance-optimized data transformation for cluster analysis in biomedical data (EDOtrans). BMC Bioinform. 23(1): 233 (2022) - 2020
- [j4]Alfred Ultsch, Jörn Lötsch:
The Fundamental Clustering and Projection Suite (FCPS): A Dataset Collection to Test the Performance of Clustering and Data Projection Algorithms. Data 5(1): 13 (2020)
2010 – 2019
- 2019
- [j3]Catharina Lippmann, Alfred Ultsch, Jörn Lötsch:
Computational functional genomics-based reduction of disease-related gene sets to their key components. Bioinform. 35(14): 2362-2370 (2019) - 2017
- [j2]Alfred Ultsch, Jörn Lötsch:
Machine-learned cluster identification in high-dimensional data. J. Biomed. Informatics 66: 95-104 (2017) - 2016
- [c2]Alfred Ultsch, Martin Behnisch, Jörn Lötsch:
ESOM Visualizations for Quality Assessment in Clustering. WSOM 2016: 39-48 - 2014
- [c1]Jörn Lötsch, Alfred Ultsch:
Exploiting the Structures of the U-Matrix. WSOM 2014: 249-257 - 2013
- [j1]Jörn Lötsch, Alfred Ultsch:
A machine-learned knowledge discovery method for associating complex phenotypes with complex genotypes. Application to pain. J. Biomed. Informatics 46(5): 921-928 (2013)
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