Publikationen

2024

• Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry

  Haghofer, A., Parlak, E., Bartel, A., Donovan, T., Assenmacher, C.-A., Bolfa, P., … Bertram, C. (2024). Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry. Veterinary Pathology, 03009858241295399. http://doi.org/10.1177/03009858241295399

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  Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics can improve reproducibility, but current manual methods are time-consuming. The aim of this study was to explore the limitations of estimates and develop alternative morphometric solutions for canine cutaneous mast cell tumors (ccMCTs). We assessed the following nuclear evaluation methods for accuracy, reproducibility, and prognostic utility: (1) anisokaryosis estimates by 11 pathologists; (2) gold standard manual morphometry of at least 100 nuclei; (3) practicable manual morphometry with stratified sampling of 12 nuclei by 9 pathologists; and (4) automated morphometry using deep learning–based segmentation. The study included 96 ccMCTs with available outcome information. Inter-rater reproducibility of anisokaryosis estimates was low (k = 0.226), whereas it was good (intraclass correlation = 0.654) for practicable morphometry of the standard deviation (SD) of nuclear size. As compared with gold standard manual morphometry (area under the ROC curve [AUC] = 0.839, 95% confidence interval [CI] = 0.701–0.977), the prognostic value (tumor-specific survival) of SDs of nuclear area for practicable manual morphometry and automated morphometry were high with an AUC of 0.868 (95% CI = 0.737–0.991) and 0.943 (95% CI = 0.889–0.996), respectively. This study supports the use of manual morphometry with stratified sampling of 12 nuclei and algorithmic morphometry to overcome the poor reproducibility of estimates. Further studies are needed to validate our findings, determine inter-algorithmic reproducibility and algorithmic robustness, and explore tumor heterogeneity of nuclear features in entire tumor sections.

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  • Personenseiten

    • Aubreville, Marc

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Journal Article
  • • Andreas Haghofer
    • Eda Parlak
    • Alexander Bartel
    • Taryn Donovan
    • Charles-Antoine Assenmacher
    • Pompei Bolfa
    • Michael Dark
    • Andrea Fuchs-Baumgartinger
    • Andrea Klang
    • Kathrin Jäger
    • Robert Klopfleisch
    • Sophie Merz
    • Barbara Richter
    • Yvonne Schulman
    • Hannah Janout
    • Jonathan Ganz
    • Josef Scharinger
    • Marc Aubreville
    • Stephan Winkler
    • Matti Kiupel
    • Christof Bertram

• Vortrag: Die Entdeckung des Higgs-Teilchens

  Vest, A. (2024). Vortrag: Die Entdeckung des Higgs-Teilchens.

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    • Vest, Anja

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2024
  • Miscellaneous
  • • Anja Vest

• Impact of motions on floating wind turbine power production

  Garcia-Sagrado, A., Schlipf, D., Brovia, S. P., Burstein, J., & Yoshinaga, T. (2024). Impact of motions on floating wind turbine power production. In Journal of Physics: Conference Series. http://doi.org/10.1088/1742-6596/2767/6/062034

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    • Schlipf, David

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  • 2024
  • Conference Paper
  • • Ana Garcia-Sagrado
    • David Schlipf
    • Santiago Brovia
    • Justin Burstein
    • Tsuyoshi Yoshinaga

• A federated learning approach to QoS forecasting in cellular vehicular communications: Approaches and empirical evidence

  Baganal-Krishna, N., Lübben, R., Liotou, E., Katsaros, K. V., & Rizk, A. (2024). A federated learning approach to QoS forecasting in cellular vehicular communications: Approaches and empirical evidence. Computer Networks, 242, 110239. http://doi.org/https://doi.org/10.1016/j.comnet.2024.110239

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  QoS forecasting for cellular vehicular communications allows cooperative, connected and automated mobility applications to tailor their behavior to the expected communication conditions on the road. In a nutshell, vehicles may, for example, execute cooperative maneuvers if the communication quality of service is only above a certain quantitative level whereas if not they revert to the individual autonomous mode. In this paper, we propose and show empirical methods for estimating packet-based QoS metrics obtained from 5G network measurements with a direct application to vehicular applications. As many distributed vehicular applications possess strict QoS requirements, we focus here on bounding packet-based statistical QoS quantiles, specifically for latency and loss. Our approach is based on training regression neural networks in a federated learning fashion and show that it can obtain predictions on par with centralized training without the vehicles needing to transmit raw measurement data. In contrast to QoS prediction using physical layer information, we briefly discuss the embedding of such much simpler application-level service within the 5G architecture. We also validate our approach through recovering classical closed-form delay quantiles that are obtained from analytical models of simple queueing systems. We show that our approach goes beyond these simple models in that it provides quantile estimates for the complex scenario of cellular vehicle communications and under different application traffic patterns including empirical data traffic traces as well as 5G testbed measurements.

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    • Lübben, Ralf

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 4: Wirtschaft

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  • 2024
  • Journal Article
  • • Nehal Baganal-Krishna
    • Ralf Lübben
    • Eirini Liotou
    • Konstantinos Katsaros
    • Amr Rizk
  • • Predictive QoS
    • Vehicular communications
    • Federated learning
    • 5G measurements

• Problem Solving Strategies in Physical and Mental Rotation

  Wetzel, S., & Bertel, S. (2024). Problem Solving Strategies in Physical and Mental Rotation. Spatial Cognition Conference 2024. Dublin.

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    • Bertel, Sven

  • Forschungsprojekt

    • Kompetenzen für eine digitale Welt: partizipative Entwicklung von Apps zum Training räumlicher Fähigkeiten im Unterricht

  • Abteilung/Einrichtung

    • CIVU – Center for Interaction, Visualization and Usability

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Human-Computer-Interaction

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Conference Proceedings
  • • Stefanie Wetzel
    • Sven Bertel

• An Interdisciplinary Perspective on AI-Supported Decision Making in Medicine

  Ammeling, J., Aubreville, M., Fritz, A., Kießig, A., Krügel, S., & Uhl, M. (2024). An Interdisciplinary Perspective on AI-Supported Decision Making in Medicine. Technology in Society, 102791.

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    • Aubreville, Marc

  • Forschungsprojekt

    • (mu)ROMI: Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research
    • CIVU – Center for Interaction, Visualization and Usability

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Journal Article
  • • Jonas Ammeling
    • Marc Aubreville
    • Alexis Fritz
    • Angelika Kießig
    • Sebastian Krügel
    • Matthias Uhl

• EXERGY-BASED METHODS FOR HEAT PUMPS

  Hofmann, M., Freißmann, J., Fritz, M., Alexe, J. H., Witte, F., & Tsatsaronis, G. (2024). EXERGY-BASED METHODS FOR HEAT PUMPS. In Proceedings of the 7th International Seminar on ORC Power System (ORC 2023) (S. 553–562). Editorial Universidad de Sevilla. http://doi.org/10.12795/9788447227457_92

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    • Freißmann, Jonas
    • Fritz, Malte
    • Witte, Francesco

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  • 2024
  • Book Chapter
  • • Mathias Hofmann
    • Jonas Freißmann
    • Malte Fritz
    • Jeremias Alexe
    • Francesco Witte
    • George Tsatsaronis

• Data-Driven Analysis of Physical and Mental Rotation Strategies

  Wetzel, S., & Bertel, S. (2024). Data-Driven Analysis of Physical and Mental Rotation Strategies. CogSci 2025 conference. Rotterdam: Cognitive Science Society.

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  Studying physical rotation (i.e., rotation tasks during which figures can be physically rotated, such as through gestures) can offer insights also into problem solving processes at work during mental rotation. We present a novel method for behavioral pattern analysis which we applied to data from 2,999 physical rotation tasks gathered in-class from 50 secondary school students. The method uses normalized, resampled, time-dependent data on angular offsets between figures over time and agglomerative, correlation-based clustering. Each cluster represents a distinct behavioral pattern and its respective prototype a problem solving strategy. Results indicate that multiple strategies were employed: The dominant strategy matches the classical model of mental rotation, in which angular offsets between figures are decreased over time. For the secondary strategy, angular offsets were actually increased. A subsequent analysis shows that the secondary strategy was more frequently used for symmetric figures, possibly indicating problems with correctly matching segments across figures.

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    • Bertel, Sven

  • Forschungsprojekt

    • Kompetenzen für eine digitale Welt: partizipative Entwicklung von Apps zum Training räumlicher Fähigkeiten im Unterricht

  • Abteilung/Einrichtung

    • CIVU – Center for Interaction, Visualization and Usability

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Human-Computer-Interaction

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Conference Proceedings
  • • Stefanie Wetzel
    • Sven Bertel

• Investigation of asymmetric SVM switching patterns with minor flux loops in inverter fed induction motors

  Königs, M., & Löhlein, B. (2024). Investigation of asymmetric SVM switching patterns with minor flux loops in inverter fed induction motors. Research gate, open access. http://doi.org/http://dx.doi.org/10.13140/RG.2.2.21923.26407

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  • 2024
  • Journal Article
  • • Mike Königs
    • Bernd Löhlein

• Wasserstoff in der kommunalen Wärmeplanung. Lessons learned aus Schleswig-Holstein

  Blohm, M., Braunger, I., Hoffmann, I., & Semp, J. (2024). Wasserstoff in der kommunalen Wärmeplanung. Lessons learned aus Schleswig-Holstein. Abgerufen von https://coaltransitions.org/publications/wasserstoff-in-der-kommunalen-warmeplanung/

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  • Personenseiten

    • Blohm, Marina

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2024
  • Report
  • • Marina Blohm
    • Isabell Braunger
    • Ilka Hoffmann
    • Josephine Semp