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.
| Author of HS Reutlingen | Martínez 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): |  Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International |
