Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies.

Juarez-Orozco, Luis Eduardo; Klén, Riku; Niemi, Mikael; Ruijsink, Bram; Daquarti, Gustavo; van Es, Rene; Benjamins, Jan-Walter; Yeung, Ming Wai; van der Harst, Pim; Knuuti, Juhani

Juarez-Orozco, Luis Eduardo; Klén, Riku; Niemi, Mikael; Ruijsink, Bram; Daquarti, Gustavo; van Es, Rene; Benjamins, Jan-Walter; Yeung, Ming Wai; van der Harst, Pim; Knuuti, Juhani.

Afiliación

Juarez-Orozco LE; Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Klén R; Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
Niemi M; Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Ruijsink B; Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
Daquarti G; Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520, Turku, Finland.
van Es R; Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Benjamins JW; Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas' Hospital, London, UK.
Yeung MW; Department of Artificial Intelligence, UMA-Health, Buenos Aires, Argentina.
van der Harst P; Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.
Knuuti J; Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.

Curr Cardiol Rep ; 24(4): 307-316, 2022 04.

Article en En | MEDLINE | ID: mdl-35171443

Asunto(s)

Cardiología; Enfermedades Cardiovasculares; Inteligencia Artificial; Cardiología/métodos; Enfermedades Cardiovasculares/diagnóstico por imagen; Humanos; Aprendizaje Automático

Palabras clave

Artificial intelligence; Deep learning; Nuclear cardiology; Risk prediction

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Cardiología / Enfermedades Cardiovasculares Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Curr Cardiol Rep Asunto de la revista: CARDIOLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Estados Unidos

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google