Carl Böck

554 total citations
22 papers, 361 citations indexed

About

Carl Böck is a scholar working on Cardiology and Cardiovascular Medicine, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Carl Böck has authored 22 papers receiving a total of 361 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Cardiology and Cardiovascular Medicine, 6 papers in Cognitive Neuroscience and 4 papers in Artificial Intelligence. Recurrent topics in Carl Böck's work include ECG Monitoring and Analysis (6 papers), EEG and Brain-Computer Interfaces (6 papers) and Machine Learning in Healthcare (3 papers). Carl Böck is often cited by papers focused on ECG Monitoring and Analysis (6 papers), EEG and Brain-Computer Interfaces (6 papers) and Machine Learning in Healthcare (3 papers). Carl Böck collaborates with scholars based in Austria, Hungary and Croatia. Carl Böck's co-authors include Jens Meier, Stephan Kolassa, Alexander Karabatsiakis, Enrico Calzia, Iris‐Tatjana Kolassa, Detlef E. Dietrich, Thomas Tschoellitsch, Mario Huemer, Péter Kovács and Karin Schwarzbauer and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, Anesthesia & Analgesia and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Carl Böck

22 papers receiving 356 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Carl Böck Austria 9 75 66 55 50 46 22 361
Vikas Pareek India 13 19 0.3× 181 2.7× 27 0.5× 51 1.0× 18 0.4× 40 754
Mohammad Reza Raoufy Iran 17 63 0.8× 62 0.9× 154 2.8× 152 3.0× 165 3.6× 80 915
Sam Miller United Kingdom 12 153 2.0× 286 4.3× 63 1.1× 154 3.1× 80 1.7× 27 874
Aihua Ou China 15 17 0.2× 146 2.2× 24 0.4× 57 1.1× 24 0.5× 54 638
Fang Han China 12 10 0.1× 46 0.7× 33 0.6× 71 1.4× 177 3.8× 46 500
Antonio Jeréz-Calero Spain 10 55 0.7× 69 1.0× 6 0.1× 31 0.6× 24 0.5× 17 352
Akiva Leibowitz United States 16 19 0.3× 131 2.0× 66 1.2× 96 1.9× 16 0.3× 33 656
Xiao Guo China 12 20 0.3× 211 3.2× 46 0.8× 36 0.7× 166 3.6× 23 668
Beata Graff Poland 12 14 0.2× 36 0.5× 211 3.8× 33 0.7× 108 2.3× 43 493

Countries citing papers authored by Carl Böck

Since Specialization
Citations

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

Fields of papers citing papers by Carl Böck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Carl Böck. 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 Carl Böck. The network helps show where Carl Böck may publish in the future.

Co-authorship network of co-authors of Carl Böck

This figure shows the co-authorship network connecting the top 25 collaborators of Carl Böck. A scholar is included among the top collaborators of Carl Böck 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 Carl Böck. Carl Böck 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.
Tschoellitsch, Thomas, Philipp Moser, Philipp Seidl, et al.. (2024). Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study. Journal of Clinical Anesthesia. 99. 111654–111654. 2 indexed citations
2.
Böck, Carl, et al.. (2024). Detection of Subtle ECG Changes Despite Superimposed Artifacts by Different Machine Learning Algorithms. Algorithms. 17(8). 360–360. 1 indexed citations
3.
Böck, Carl, et al.. (2024). Weighted Hermite Variable Projection Networks for Classifying Visually Evoked Potentials. IEEE Transactions on Neural Networks and Learning Systems. 36(7). 12415–12428. 4 indexed citations
4.
Tschoellitsch, Thomas, Philipp Moser, Philipp Seidl, et al.. (2024). Potential Predictors for Deterioration of Renal Function After Transfusion. Anesthesia & Analgesia. 138(3). 645–654. 1 indexed citations
5.
Böck, Carl, et al.. (2023). Joint Self-Interference Cancellation and Data Estimation for OFDM Based Full-Duplex Communication Systems. TU/e Research Portal. 1. 345–352. 1 indexed citations
6.
Böck, Carl, et al.. (2023). Acquired Factor XIII Deficiency Is Common during ECMO Therapy and Associated with Major Bleeding Events and Transfusion Requirements. Journal of Clinical Medicine. 12(12). 4115–4115. 9 indexed citations
7.
Böck, Carl, et al.. (2023). Variability of expert assessments of ECG time domain parameters. PubMed. 2(2). e0020–e0020. 2 indexed citations
8.
Tschoellitsch, Thomas, Philipp Seidl, Carl Böck, et al.. (2023). Using emergency department triage for machine learning-based admission and mortality prediction. European Journal of Emergency Medicine. 30(6). 408–416. 10 indexed citations
9.
Tschoellitsch, Thomas, et al.. (2022). Machine learning-based prediction of massive perioperative allogeneic blood transfusion in cardiac surgery. European Journal of Anaesthesiology. 39(9). 766–773. 12 indexed citations
10.
Böck, Carl, et al.. (2022). Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. Journal of Medical Systems. 46(5). 23–23. 23 indexed citations
11.
Böck, Carl, et al.. (2022). Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities. JMIR Medical Informatics. 10(10). e38557–e38557. 6 indexed citations
12.
Kovács, Péter, Carl Böck, Thomas Tschoellitsch, Mario Huemer, & Jens Meier. (2022). Diagnostic quality assessment for low-dimensional ECG representations. Computers in Biology and Medicine. 150. 106086–106086. 2 indexed citations
13.
Böck, Carl, et al.. (2021). Machine Learning Based Color Classification by Means of Visually Evoked Potentials. Applied Sciences. 11(24). 11882–11882. 3 indexed citations
14.
Böck, Carl, Péter Kovács, Pablo Laguna, Jens Meier, & Mario Huemer. (2021). ECG Beat Representation and Delineation by Means of Variable Projection. IEEE Transactions on Biomedical Engineering. 68(10). 2997–3008. 41 indexed citations
15.
Böck, Carl, et al.. (2021). Color classification of visually evoked potentials by means of Hermite functions. 2021 55th Asilomar Conference on Signals, Systems, and Computers. 251–255. 5 indexed citations
16.
Mitterecker, Andreas, Axel Hofmann, Kevin M. Trentino, et al.. (2020). Machine learning–based prediction of transfusion. Transfusion. 60(9). 1977–1986. 32 indexed citations
17.
Tschoellitsch, Thomas, Martin W. Dünser, Carl Böck, Karin Schwarzbauer, & Jens Meier. (2020). Machine Learning Prediction of SARS-CoV-2 Polymerase Chain Reaction Results with Routine Blood Tests. Laboratory Medicine. 52(2). 146–149. 27 indexed citations
18.
Lang, Oliver, Carl Böck, Mario Huemer, & Christian Hofbauer. (2019). Increasing the Bandwidth Efficiency in UW-OFDM. 21. 1857–1861. 3 indexed citations
19.
Kovács, Péter, Carl Böck, Jens Meier, & Mario Huemer. (2017). ECG segmentation using adaptive hermite functions. 43. 1476–1480. 6 indexed citations
20.
Karabatsiakis, Alexander, Carl Böck, Stephan Kolassa, et al.. (2014). Mitochondrial respiration in peripheral blood mononuclear cells correlates with depressive subsymptoms and severity of major depression. Translational Psychiatry. 4(6). e397–e397. 160 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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Rankless by CCL
2026