Anke Meyer‐Baese

3.6k total citations
193 papers, 2.3k citations indexed

About

Anke Meyer‐Baese is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Cognitive Neuroscience. According to data from OpenAlex, Anke Meyer‐Baese has authored 193 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 70 papers in Artificial Intelligence, 48 papers in Radiology, Nuclear Medicine and Imaging and 47 papers in Cognitive Neuroscience. Recurrent topics in Anke Meyer‐Baese's work include Neural Networks and Applications (40 papers), MRI in cancer diagnosis (27 papers) and Functional Brain Connectivity Studies (26 papers). Anke Meyer‐Baese is often cited by papers focused on Neural Networks and Applications (40 papers), MRI in cancer diagnosis (27 papers) and Functional Brain Connectivity Studies (26 papers). Anke Meyer‐Baese collaborates with scholars based in United States, Germany and Austria. Anke Meyer‐Baese's co-authors include Axel Wismüller, Simon Y. Foo, Amirhessam Tahmassebi, Henning Scheich, Frank W. Ohl, Sergei S. Pilyugin, Fabian J. Theis, O. Lange, Katja Pinker and Uwe Meyer‐Baese and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Cancer Research.

In The Last Decade

Anke Meyer‐Baese

180 papers receiving 2.3k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Anke Meyer‐Baese 784 705 449 438 268 193 2.3k
Evrim Acar 512 0.7× 365 0.5× 118 0.3× 238 0.5× 248 0.9× 60 2.4k
Vasileios Megalooikonomou 531 0.7× 299 0.4× 168 0.4× 219 0.5× 485 1.8× 136 1.9k
James Ford 477 0.6× 260 0.4× 299 0.7× 128 0.3× 313 1.2× 74 2.0k
Jin Cao 473 0.6× 171 0.2× 933 2.1× 196 0.4× 123 0.5× 83 2.0k
Habiboulaye Amadou Boubacar 798 1.0× 131 0.2× 126 0.3× 181 0.4× 477 1.8× 6 1.8k
Steven K. Rogers 1.2k 1.6× 582 0.8× 152 0.3× 98 0.2× 691 2.6× 164 2.9k
Barnabás Póczos 1.5k 1.9× 167 0.2× 133 0.3× 116 0.3× 736 2.7× 120 3.3k
Santosh S. Venkatesh 1.1k 1.4× 87 0.1× 464 1.0× 183 0.4× 254 0.9× 76 1.9k
豊 松尾 1.7k 2.2× 194 0.3× 167 0.4× 136 0.3× 1.5k 5.6× 5 3.6k
Pengjiang Qian 942 1.2× 410 0.6× 66 0.1× 388 0.9× 722 2.7× 101 2.2k

Countries citing papers authored by Anke Meyer‐Baese

Since Specialization
Citations

This map shows the geographic impact of Anke Meyer‐Baese'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 Anke Meyer‐Baese with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anke Meyer‐Baese more than expected).

Fields of papers citing papers by Anke Meyer‐Baese

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anke Meyer‐Baese. 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 Anke Meyer‐Baese. The network helps show where Anke Meyer‐Baese may publish in the future.

Co-authorship network of co-authors of Anke Meyer‐Baese

This figure shows the co-authorship network connecting the top 25 collaborators of Anke Meyer‐Baese. A scholar is included among the top collaborators of Anke Meyer‐Baese 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 Anke Meyer‐Baese. Anke Meyer‐Baese is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Jütten, Kerstin, Julius M. Kernbach, Anke Meyer‐Baese, et al.. (2025). High peritumoral network connectedness in glioblastoma reveals a distinct epigenetic signature and is associated with decreased overall survival. Neuro-Oncology. 27(10). 2564–2573.
2.
You, Wei, Anke Meyer‐Baese, Xinzhong Xu, & Qimin Zhang. (2024). The dynamics and near‐optimal controls of a dengue model with threshold policy. Mathematical Methods in the Applied Sciences. 47(17). 13313–13335.
3.
Stadlbauer, Andreas, Katarina Nikolić, Stefan Oberndorfer, et al.. (2024). Machine Learning-Based Prediction of Glioma IDH Gene Mutation Status Using Physio-Metabolic MRI of Oxygen Metabolism and Neovascularization (A Bicenter Study). Cancers. 16(6). 1102–1102. 5 indexed citations
4.
Amani, Ali Moradi, Amirhessam Tahmassebi, Andreas Stadlbauer, et al.. (2024). Controllability of Functional and Structural Brain Networks. Complexity. 2024(1).
5.
Meyer‐Baese, Anke, Kerstin Jütten, Uwe Meyer‐Baese, et al.. (2023). Controllability and Robustness of Functional and Structural Connectomic Networks in Glioma Patients. Cancers. 15(10). 2714–2714. 2 indexed citations
6.
Stadlbauer, Andreas, Franz Marhold, Stefan Oberndorfer, et al.. (2022). Radiophysiomics: Brain Tumors Classification by Machine Learning and Physiological MRI Data. Cancers. 14(10). 2363–2363. 34 indexed citations
7.
Álvarez, I., Javier Ramı́rez, J. M. Górriz, et al.. (2018). Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging. Contrast Media & Molecular Imaging. 2018. 1–11. 14 indexed citations
8.
Fernández, Daniel, Alberto A. Del Barrio, Guillermo Botella, et al.. (2017). Information fusion based techniques for HEVC. ScholarWorks (Central Washington University). 1 indexed citations
9.
Meyer‐Baese, Anke, Rodney G. Roberts, I. Álvarez, et al.. (2017). Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks. Frontiers in Computational Neuroscience. 11. 87–87. 8 indexed citations
10.
Pinker, Katja, Maria Adele Marino, Anke Meyer‐Baese, & Thomas H. Helbich. (2016). Multiparametrische und molekulare Bildgebung von Brusttumoren mit MRT und PET‑MRT. Der Radiologe. 56(7). 612–621. 7 indexed citations
11.
Emmett, Mark R., Roger A. Kroes, Joseph R. Moskal, et al.. (2013). Integrative Biological Analysis For Neuropsychopharmacology. Neuropsychopharmacology. 39(1). 5–23. 13 indexed citations
12.
Vlaic, Sebastian, Wolfgang Schmidt‐Heck, Madlen Matz‐Soja, et al.. (2012). The extended TILAR approach: a novel tool for dynamic modeling of the transcription factor network regulating the adaption to in vitro cultivation of murine hepatocytes. BMC Systems Biology. 6(1). 147–147. 12 indexed citations
13.
Althaus, Ernst, Stefan Canzar, Mark R. Emmett, et al.. (2009). Discrete fitting of hydrogen-deuterium-exchange data of overlapping fragments. Data Archiving and Networked Services (DANS). 496–502. 6 indexed citations
14.
Meyer‐Baese, Anke, et al.. (2009). Global stability analysis and robust design of multi-time-scale biological networks under parametric uncertainties. Neural Networks. 22(5-6). 658–663. 7 indexed citations
15.
Wismüller, Axel, Anke Meyer‐Baese, O. Lange, Maximilian F. Reiser, & G. Leinsinger. (2005). Cluster analysis of dynamic cerebral contrast-enhanced perfusion MRI time-series. IEEE Transactions on Medical Imaging. 25(1). 62–73. 44 indexed citations
16.
Meyer‐Baese, Anke, et al.. (2004). Topographic independent component analysis for fMRI signal detection. 1. 601–605. 14 indexed citations
17.
Wismüller, Axel, et al.. (2004). Model-free functional MRI analysis based on unsupervised clustering. Journal of Biomedical Informatics. 37(1). 10–18. 34 indexed citations
18.
Wismüller, Axel, et al.. (2004). Fully automated biomedical image segmentation by self-organized model adaptation. Neural Networks. 17(8-9). 1327–1344. 42 indexed citations
19.
Meyer‐Baese, Anke. (2003). Pattern Recognition in Medical Imaging. 31 indexed citations
20.
Meyer‐Baese, Anke. (1995). Quadratic-Type Lyapunov Functions for Competitive Neural Networks with Different Time-Scales. Neural Information Processing Systems. 8. 337–343. 2 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.

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