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Deployment of artificial intelligence models for sleep apnea recognition in the sleep laboratory

  • There are a large number of scientific publications that focus on the development and evaluation of artificial intelligence (AI) models for the detection of various pathologies in the field of sleep medicine. However, most of these publications do not show the process or methodology to be followed for the final deployment of these models in a complete diagnostic system (in terms of software and hardware). This is a major drawback when translating from the development or research environment to the real clinical setting. This work focuses on a methodology for deploying an AI model for sleep apnea detection with the end user in mind: the clinician. For the deployment, the transmission of data between the device, the cloud platform and the machine learning server, as well as the protocols used, were considered. In addition, the storage and visualization of the data has been taken into account so that it can be analyzed accurately by experts.

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Metadaten
Author of HS ReutlingenMartínez Madrid, Natividad; Serrano Alarcón, Ángel
URN:urn:nbn:de:bsz:rt2-opus4-53108
DOI:https://doi.org/10.1016/j.procs.2024.09.665
ISSN:1877-0509
Erschienen in:Procedia computer science
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Conference proceeding
Language:English
Publication year:2024
Tag:artificial intelligence; deep learning; sleep disorder; sleep/wake state
Volume:246
Page Number:8
First Page:5388
Last Page:5395
DDC classes:004 Informatik
Open access?:Ja
Licence (German):License Logo  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International