Zobrazeno 1 - 10
of 26
pro vyhledávání: '"A. Chimenea-Toscano"'
Autor:
Oprescu, A.M., Miró-Amarante, G., García-Díaz, L., Rey, V.E., Chimenea-Toscano, A., Martínez-Martínez, R., Romero-Ternero, M.C.
Publikováno v:
In Information Fusion July 2022 83-84:53-78
Publikováno v:
Revista Colombiana de Obstetricia y Ginecología, Vol 72, Iss 2 (2021)
Objetivos: reportar el caso de una paciente con diagnóstico prenatal de atresia de yeyuno y hacer una revisión de la literatura en torno al resultado y al diagnóstico de esta entidad, implementando el uso de métodos no convencionales: ecografía
Externí odkaz:
https://doaj.org/article/4d31565fd211406cbcd71eff5da29ea5
Autor:
A.M. Oprescu, G. Miró-Amarante, L. García-Díaz, V.E. Rey, A. Chimenea-Toscano, R. Martínez-Martínez, M.C. Romero-Ternero
Publikováno v:
Information Fusion. :53-78
A medical field that is increasingly benefiting from Artificial Intelligence applications is Gyne- cology and Obstetrics. In previous work, we exposed that Artificial Intelligence (AI) technology and obstetric control by physicians can enhance pregna
Autor:
Pablo Caro-Domínguez, Teresa Victoria, Pierluigi Ciet, Estrella de la Torre, Ángel Chimenea Toscano, Lutgardo García Diaz, José Antonio Sainz-Bueno
Publikováno v:
Pediatric Radiology. Springer-Verlag
Congenital thoracic anomalies are uncommon malformations that require a precise diagnosis to guide parental counseling and possible prenatal treatment. Prenatal ultrasound (US) is the gold standard imaging modality to first detect and characterize th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddec47c9ab9051662c528b4b5857684e
https://pure.eur.nl/en/publications/512b7b1f-dd86-42bc-9619-dafeb80e55b8
https://pure.eur.nl/en/publications/512b7b1f-dd86-42bc-9619-dafeb80e55b8
Autor:
Chimenea-Toscano, Ángel1,2, García-Díaz, Lutgardo1, Antiñolo-Gil, Guillermo1,2,3 gantinolo@us.es
Publikováno v:
Revista Colombiana de Obstetricia y Ginecologia. abr-jun2021, Vol. 72 Issue 2, p202-209. 8p.
Akademický článek
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Autor:
Lola Gómez-Jemes, Andreea Madalina Oprescu, Ángel Chimenea-Toscano, Lutgardo García-Díaz, María del Carmen Romero-Ternero
Publikováno v:
Electronics; Volume 11; Issue 19; Pages: 3240
The use of artificial intelligence in healthcare in general and in obstetrics and gynecology in particular has great potential. Specifically, machine learning methods could help improve the health and well-being of pregnant women, closely monitoring