Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Antonio J. Rodriguez-Almeida"'
Autor:
Alejandro Deniz-Garcia, Himar Fabelo, Antonio J Rodriguez-Almeida, Garlene Zamora-Zamorano, Maria Castro-Fernandez, Maria del Pino Alberiche Ruano, Terje Solvoll, Conceição Granja, Thomas Roger Schopf, Gustavo M Callico, Cristina Soguero-Ruiz, Ana M Wägner
Publikováno v:
Journal of Medical Internet Research, Vol 25, p e44030 (2023)
The use of artificial intelligence (AI) and big data in medicine has increased in recent years. Indeed, the use of AI in mobile health (mHealth) apps could considerably assist both individuals and health care professionals in the prevention and manag
Externí odkaz:
https://doaj.org/article/f4c3411e05344f27967eb2c53ae713fb
Autor:
'Daniel Eneriz, Antonio J. Rodriguez-Almeida, Himar Fabelo, Samuel Ortega, Francisco Balea-Fernandez, Nicolás J. Medrano, Belén Calvo, Gustavo M. Callico\\'
Publikováno v:
Computing in Cardiology Conference (CinC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac10f9d772ba9a43798af74e6e99e901
https://doi.org/10.22489/cinc.2022.266
https://doi.org/10.22489/cinc.2022.266
Autor:
Antonio J. Rodriguez-Almeida, Himar Fabelo, Samuel Ortega, Alejandro Deniz, Francisco J. Balea-Fernandez, Eduardo Quevedo, Cristina Soguero-Ruiz, Ana M. Wagner, Gustavo M. Callico
Publikováno v:
IEEE journal of biomedical and health informatics.
The increasing prevalence of chronic non-communicable diseases makes it a priority to develop tools for enhancing their management. On this matter, Artificial Intelligence algorithms have proven to be successful in early diagnosis, prediction and ana
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0998da7c960369d0698726e13afe8c52
https://pubmed.ncbi.nlm.nih.gov/35930509
https://pubmed.ncbi.nlm.nih.gov/35930509
Autor:
Daniel Enériz, Antonio J. Rodriguez-Almeida, Himar Fabelo, Nicolás Medrano, Belén Calvo, Gustavo M. Callico
Publikováno v:
Jornada de Jóvenes Investigadores del I3A. 10
Un sistema de asistencia al diagnóstico de enfermedades cardiovasculares requiere de precisión y respuesta en tiempo real, algo que se puede alcanzar gracias a la implementación de modelos deep learning on the edge. En este trabajo se presenta la
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6edb527e028df90e0e089c980e4b611a
https://doi.org/10.26754/jjii3a.20226995
https://doi.org/10.26754/jjii3a.20226995