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This paper is in the following e-collection/theme issue:

New Technologies (121) Design and Usability of Medical Devices (165) Artificial Intelligence (2437) Urology (47) AI Applications in Biomedical Engineering (21)

Published on in Vol 14 (2026)

This is a member publication of University of Duisburg-Essen

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80829, first published .
From Flow to Feature Using a Proof-of-Concept Spectral-Driven Machine Learning Approach Using Smart Urinary and Drainage Catheter Systems: Algorithm Development and Validation

From Flow to Feature Using a Proof-of-Concept Spectral-Driven Machine Learning Approach Using Smart Urinary and Drainage Catheter Systems: Algorithm Development and Validation

From Flow to Feature Using a Proof-of-Concept Spectral-Driven Machine Learning Approach Using Smart Urinary and Drainage Catheter Systems: Algorithm Development and Validation

Authors of this article:

Leonardo Poggi1, 2 Author Orcid Image ;   Anastasia Meckler3 Author Orcid Image ;   Sebastian Künert3 Author Orcid Image ;   Julia Jeske3 Author Orcid Image ;   Ramsi Siaj3 Author Orcid Image ;   Thanusiah Selvamoorthy3 Author Orcid Image ;   Michael Fabian Berger3 Author Orcid Image ;   Felix Nensa1, 2 Author Orcid Image ;   Judith Kohnke1, 2 Author Orcid Image ;   Bernadette Hosters4 Author Orcid Image ;   Jennifer Brendt-Müller4 Author Orcid Image ;   Mario Roser5 Author Orcid Image ;   René Hosch1, 2 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Leonardo Poggi   1, 2 , MSc ;   Anastasia Meckler   3 ;   Sebastian Künert   3 ;   Julia Jeske   3 , Dr rer nat ;   Ramsi Siaj   3 , MDRA, Dr rer nat ;   Thanusiah Selvamoorthy   3 , BSc ;   Michael Fabian Berger   3 , MD ;   Felix Nensa   1, 2 , MD ;   Judith Kohnke   1, 2 , MSc ;   Bernadette Hosters   4 , MSc ;   Jennifer Brendt-Müller   4 , MSc ;   Mario Roser   5 * , MSc ;   René Hosch   1, 2 * , PhD

1 Institute of Diagnostic and Interventional Radiology and Neuroradiology, Essen University Hospital, Essen, Germany

2 Institute for Artificial Intelligence in Medicine (IKIM), Essen University Hospital, Essen, Germany

3 Department of Pediatric Surgery, Essen University Hospital, Essen, Germany

4 Department of Nursing Development and Nursing Research, Essen University Hospital, Essen, Germany

5 Elixion Medical GmbH, Düsseldorf, Germany

*these authors contributed equally

Corresponding Author:

  • René Hosch, PhD
  • Institute of Diagnostic and Interventional Radiology and Neuroradiology, Essen University Hospital
  • Hufelandstraße 55
  • Essen 45147
  • Germany
  • Phone: 43 20172377817
  • Email: rene.hosch@uk-essen.de