Lucas Plagwitz

According to our database, Lucas Plagwitz authored at least 8 papers between 2020 and 2023.

Collaborative distances:

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

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