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

New Methods (1184) Clinical Informatics (1454) Clinical Information and Decision Making (2084) Telehealth and Telemonitoring (2214) Tools, Programs and Algorithms (412) Decision Support for Health Professionals (1649) Machine Learning (2251) Alarm Fatigue (27) Data Science (396) Intensive Care Unit (ICU) (168)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65961, first published .
Developing a Scalable Annotation Method for Large Datasets That Enhances Alarms With Actionability Data to Increase Informativeness: Mixed Methods Approach

Developing a Scalable Annotation Method for Large Datasets That Enhances Alarms With Actionability Data to Increase Informativeness: Mixed Methods Approach

Developing a Scalable Annotation Method for Large Datasets That Enhances Alarms With Actionability Data to Increase Informativeness: Mixed Methods Approach

Authors of this article:

Sophie Anne Inès Klopfenstein1, 2 Author Orcid Image ;   Anne Rike Flint1 Author Orcid Image ;   Patrick Heeren1, 3 Author Orcid Image ;   Mona Prendke1 Author Orcid Image ;   Amin Chaoui1 Author Orcid Image ;   Thomas Ocker3 Author Orcid Image ;   Jonas Chromik4 Author Orcid Image ;   Bert Arnrich4 Author Orcid Image ;   Felix Balzer1, 5 Author Orcid Image ;   Akira-Sebastian Poncette1, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics Author Video

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  3. Schrader N, Meißner B, Fischer P, Röder D, Ertl M, Meybohm P, Schmid B. Extraction and processing of intensive care chart data from a patient data management system. Frontiers in Digital Health 2026;8 View