TY  - GEN 
AU  - Amado Caballero, Patricia
AU  - Garmendia Leiza, José Ramón
AU  - Aguilar García, M. D.
AU  - Martínez Fernández de Septiem, C.
AU  - San José Revuelta, Luis Miguel
AU  - García Ruano, A.
AU  - Alberola López, Carlos
AU  - Casaseca de la Higuera, Juan Pablo
PY  - 2024
SN  - 979-8-3503-7149-9
UR  - https://uvadoc.uva.es/handle/10324/72906
AB  - This study explores the feasibility of employing eXplainable Artificial Intelligence XAI methodologies for  the analysis of cough patterns in respiratory diseases. A cohort of 20 adult patients, all presenting persistent cough as a symptom of...
LA  - eng
PB  - IEEE, Institute of Electrical and Electronics Engineers
KW  - Detección
KW  - CAD
KW  - Procesado de señal
KW  - Machine learning
KW  - Deep learning
KW  - Respiratory diseases
KW  - cough
KW  - audio analysis
KW  - CNN
KW  - XAI
KW  - occlusion maps
TI  - Audio cough analysis by parametric modelling of weighted spectrograms to interpret the output of convolutional neural networks
DO  - 10.1109/EMBC53108.2024.10781781
ER  -