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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.

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Author of HS ReutlingenMartínez Madrid, Natividad; Serrano Alarcón, Ángel
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
Publication year:2024
Page Number:4
First Page:15
Last Page:18
DDC classes:610 Medizin, Gesundheit
Open access?:Nein
Licence (German):License Logo  In Copyright - Urheberrechtlich geschützt