TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Serrano Alarcón, Ángel
A1  - Martínez Madrid, Natividad
A1  - Seepold, Ralf
T1  - Influence of gender and age distinction on patient data for sleep apnea detection using artificial intelligence models
JF  - Models and Applications for Embedded Systems
N2  - 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.
KW  - Artificial intelligence models
KW  - Apnea detection
Y1  - 2023
UR  - www.dii.univpm.it/MAES-2023
SN  - 978-88-87548-00-6
SB  - 978-88-87548-00-6
SP  - 15
EP  - 18
PB  - Università Politecnica delle Marche, Dipartimento di Ingegneria dell’Informazione
CY  - Ancona, Italy
ER  -