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Computational analysis of cardiac structure and function in congenital heart disease: Translating discoveries to clinical strategies.
Forsch, Nickolas; Govil, Sachin; Perry, James C; Hegde, Sanjeet; Young, Alistair A; Omens, Jeffrey H; McCulloch, Andrew D.
Afiliação
  • Forsch N; Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
  • Govil S; Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
  • Perry JC; Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
  • Hegde S; Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
  • Young AA; Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
  • Omens JH; Department of Biomedical Engineering, King's College London, London, UK.
  • McCulloch AD; Department of Anatomy and Medical Imaging, University of Auckland, Auckland, NZ.
J Comput Sci ; 522021 May.
Article em En | MEDLINE | ID: mdl-34691293
ABSTRACT
Increased availability and access to medical image data has enabled more quantitative approaches to clinical diagnosis, prognosis, and treatment planning for congenital heart disease. Here we present an overview of long-term clinical management of tetralogy of Fallot (TOF) and its intersection with novel computational and data science approaches to discovering biomarkers of functional and prognostic importance. Efforts in translational medicine that seek to address the clinical challenges associated with cardiovascular diseases using personalized and precision-based approaches are then discussed. The considerations and challenges of translational cardiovascular medicine are reviewed, and examples of digital platforms with collaborative, cloud-based, and scalable design are provided.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Comput Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: J Comput Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos