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: | Ángel Serrano Alarcón, Natividad Martínez MadridORCiD, Ralf SeepoldORCiDGND |
|---|---|
| URL: | http://www.dii.univpm.it/MAES-2023 |
| ISBN: | 978-88-87548-00-6 |
| Parent Title (English): | Models and Applications for Embedded Systems |
| Publisher: | Università Politecnica delle Marche, Dipartimento di Ingegneria dell’Informazione |
| Place of publication: | Ancona, Italy |
| Document Type: | Article |
| Language: | English |
| Year of Publication: | 2023 |
| Release Date: | 2024/01/12 |
| Tag: | Artificial intelligence models; Apnea detection |
| First Page: | 15 |
| Last Page: | 18 |
| Institutes: | Institut für Angewandte Forschung - IAF |
| DDC functional group: | 500 Naturwissenschaften und Mathematik |
| 600 Technik, Medizin, angewandte Wissenschaften | |
| Relevance: | Keine peer reviewed Publikation (Wissenschaftlicher Artikel und Aufsatz, Proceeding, Artikel in Tagungsband) |
| Open Access?: | Nein |
| Licence (German): |  Urheberrechtlich geschützt |
