Guest Editors
Dr. Hazhee Rasoul
Email: hazhee.rasoul@nhs.net
Affiliation: Guy's and St Thomas' NHS Foundation Trust, UK
Homepage:
Research Interests: Cardiac imaging, digital health
Dr. Elettra Pomiato
Email: elettra.pomiato@gstt.nhs.uk
Affiliation: Guy's and St Thomas' NHS Foundation Trust, UK
Homepage:
Research Interests: Adult Congenital Heart Disease
Summary
Artificial intelligence (AI) is being considered the next big technological wave with the potential to have a significant impact across a wide range of different fields, with congenital heart disease being no exception.
In this special issue, we will focus on how AI can be used to diagnose and manage patients with congenital heart disease. With emerging technology, there is an exciting opportunity to explore its different applications, from cardiac imaging and ECG interpretation to the risk stratification of patients with a confirmed diagnosis. However, the breadth of congenital heart disease presents a particular challenge when it comes to having an adequate dataset to train these AI models.
Submissions to this Special Issue should involve the application of AI in a cohort of patients with congenital heart disease, with a particular focus on how this can have real-world clinical utility to improve care to these patients.
Keywords
Artificial intelligence, deep learning, machine learning, convolutional neural network, congenital heart disease
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