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 congenital heart disease 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.

医学图像数据的可用性和可访问性的增加使先天性心脏病的临床诊断、预后和治疗计划能够采用更定量的方法。在这里，我们概述了先天性心脏病的长期临床管理及其与新的计算和数据科学方法的交叉，以发现具有功能和预后重要性的生物标志物。然后讨论了转化医学的努力，旨在使用个性化和基于精确的方法解决与心血管疾病相关的临床挑战。回顾了转化心血管医学的考虑和挑战，并提供了具有协作、基于云和可扩展设计的数字平台示例。