Lucas Plagwitz

According to our database, Lucas Plagwitz authored at least 13 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

The Rlign Algorithm for Enhanced Electrocardiogram Analysis through R-Peak Alignment for Explainable Classification and Clustering.

Lucas Plagwitz, Lucas Bickmann, Michael Fujarski, Alexander Brenner, Warnes Gobalakrishnan, Lars Eckardt, Antonius Büscher, Julian Varghese

CoRR, 2024

Data-driven time series analysis of sensory cortical processing using high-resolution fMRI across different studies.

Lucas Plagwitz, Sangcheon Choi, Xin Yu, Daniel Segelcke, Henriette Lambers, Esther Pogatzki-Zahn, Julian Varghese, Cornelius Faber, Bruno Pradier

Biomed. Signal Process. Control., 2024

Assessing the Reliability of Machine Learning Explanations in ECG Analysis Through Feature Attribution.

Lucas Plagwitz, Lucas Bickmann, Antonius Büscher, Julian Varghese

Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

Benchmarking Approaches: Time Series Versus Feature-Based Machine Learning in ECG Analysis on the PTB-XL Dataset.

Lucas Bickmann, Lucas Plagwitz, Julian Varghese

Proceedings of the Digital Health and Informatics Innovations for Sustainable Health Care Systems, 2024

Zero-Shot LLMs for Named Entity Recognition: Targeting Cardiac Function Indicators in German Clinical Texts.

Lucas Plagwitz, Philipp Neuhaus, Kemal Yildirim, Noah Losch, Julian Varghese, Antonius Büscher

Proceedings of the German Medical Data Sciences 2024 - Health, 2024

2023

The Necessity of Multiple Data Sources for ECG-Based Machine Learning Models.

Lucas Plagwitz, Tobias Vogelsang, Florian Doldi, Lucas Bickmann, Michael Fujarski, Lars Eckardt, Julian Varghese

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

DeepTSE: A Time-Sensitive Deep Embedding of ICU Data for Patient Modeling and Missing Data Imputation.

Michael Fujarski, Christian Porschen, Lucas Plagwitz, Daniel Stroth, Catharina Marie van Alen, Mahan Sadjadi, Raphael Weiss, Alexander Zarbock, Thilo Caspar von Groote, Julian Varghese

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

Classification of Parkinson's Disease from Voice - Analysis of Data Selection Bias.

Alexander Brenner, Catharina Marie van Alen, Lucas Plagwitz, Julian Varghese

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

Post Hoc Sample Size Estimation for Deep Learning Architectures for ECG-Classification.

Lucas Bickmann, Lucas Plagwitz, Julian Varghese

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

2022

Supporting AI-Explainability by Analyzing Feature Subsets in a Machine Learning Model.

Lucas Plagwitz, Alexander Brenner, Michael Fujarski, Julian Varghese

Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Prediction of Acute Kidney Injury in the Intensive Care Unit: Preliminary Findings in a European Open Access Database.

Michael Fujarski, Christian Porschen, Lucas Plagwitz, Alexander Brenner, Narges Ghoreishi, Patrick Thoral, Harm-Jan de Grooth, Paul W. G. Elbers, Raphael Weiss, Melanie Meersch, Alexander Zarbock, Thilo Caspar von Groote, Julian Varghese

Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

Utilizing a Non-Motor Symptoms Questionnaire and Machine Learning to Differentiate Movement Disorders.

Alexander Brenner, Lucas Plagwitz, Michael Fujarski, Tobias Warnecke, Julian Varghese

Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

2020

PHOTON - A Python API for Rapid Machine Learning Model Development.

Ramona Leenings, Nils Ralf Winter, Lucas Plagwitz, Vincent Holstein, Jan Ernsting, Jakob Steenweg, Julian Gebker, Kelvin Sarink, Daniel Emden, Dominik Grotegerd, Nils Opel, Benjamin Risse, Xiaoyi Jiang, Udo Dannlowski, Tim Hahn

CoRR, 2020