Influence of gender and age distinction on patient data for sleep apnea detection using artificial intelligence models
- The massive use of patient data for the training of artificial intelligence algorithms is common nowadays in medicine. In this scientific work, a statistical analysis of one of the most used datasets for the training of artificial intelligence models for the detection of sleep disorders is performed: sleep health heart study 2. This study focuses on determining whether the gender and age of the patients have a relevant influence to consider working with differentiated datasets based on these variables for the training of artificial intelligence models.
| Author of HS Reutlingen | Martínez Madrid, Natividad; Serrano Alarcón, Ángel |
|---|---|
| URL: | http://www.dii.univpm.it/MAES-2023 |
| ISBN: | 978-88-87548-00-6 |
| Erschienen in: | Models and applications for embedded systems |
| Publisher: | Università Politecnica delle Marche |
| Place of publication: | Ancona |
| Editor: | Massimo Conti, Simone Orcioni |
| Document Type: | Book chapter |
| Language: | English |
| Publication year: | 2024 |
| Page Number: | 4 |
| First Page: | 15 |
| Last Page: | 18 |
| DDC classes: | 610 Medizin, Gesundheit |
| Open access?: | Nein |
| Licence (German): |  In Copyright - Urheberrechtlich geschützt |
