Bastian Rieck
- Artificial Intelligence top 5%
- Epidemiology
- Radiology, Nuclear Medicine and Imaging top 10%
- Computational Theory and Mathematics top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Karsten BorgwardtMichael MoorMax HornHeike LeitteCatherine R. JutzelerChristian BockCaroline WeisAdrian Egli
- Topics
- Topological and Geometric Data Analysis (13 papers)Machine Learning in Healthcare (8 papers)Cell Image Analysis Techniques (7 papers)
- Journals
- Nature MedicineNature CommunicationsSHILAP Revista de lepidopterología
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Bastian Rieck
45 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Artificial Intelligence 406
- Epidemiology 235
- Radiology, Nuclear Medicine and Imaging 181
- Computational Theory and Mathematics 179
- Computer Vision and Pattern Recognition 151
Countries citing papers authored by Bastian Rieck
This map shows the geographic impact of Bastian Rieck'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 Bastian Rieck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bastian Rieck more than expected).
Fields of papers citing papers by Bastian Rieck
This network shows the impact of papers produced by Bastian Rieck. 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 Bastian Rieck. The network helps show where Bastian Rieck may publish in the future.
Co-authorship network of co-authors of Bastian Rieck
This figure shows the co-authorship network connecting the top 25 collaborators of Bastian Rieck. A scholar is included among the top collaborators of Bastian Rieck 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 Bastian Rieck. Bastian Rieck is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 12 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 33 | |
| 8 | Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learningbreakdown → | 140 |
| 9 | 106 | |
| 10 | 100 | |
| 11 | 11 | |
| 12 | 1 | |
| 13 | Early prediction of circulatory failure in the intensive care unit using machine learningbreakdown → | 233 |
| 14 | 104 | |
| 15 | 31 | |
| 16 | Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology | 10 |
| 17 | Temporal Convolutional Networks and Dynamic Time Warping can Drastically Improve the Early Prediction of Sepsis. | 13 |
| 18 | 31 | |
| 19 | 13 | |
| 20 | 13 |
About Bastian Rieck
Bastian Rieck is a scholar working on Family Practice, Biophysics and Computer Graphics and Computer-Aided Design, having authored 46 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (13 papers), Machine Learning in Healthcare (8 papers) and Cell Image Analysis Techniques (7 papers). The work is most often cited by research in Health Informatics (92 citations), Family Practice (40 citations) and Clinical Biochemistry (108 citations). Bastian Rieck has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Karsten Borgwardt, Michael Moor, Max Horn, Heike Leitte, Catherine R. Jutzeler, Christian Bock, Caroline Weis, Adrian Egli, Thomas Gumbsch and Dean A. Bodenham. Their work appears in journals such as Nature Medicine, Nature Communications and SHILAP Revista de lepidopterología.
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.