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A primer on artificial intelligence for the paediatric cardiologist

Published online by Cambridge University Press:  22 June 2020

Addison Gearhart Open the ORCID record for Addison Gearhart [Opens in a new window] ,
Sharib Gaffar Open the ORCID record for Sharib Gaffar [Opens in a new window]  and
Anthony C. Chang
Addison Gearhart
Affiliation:
Boston Children’s Hospital, Boston, MA02115, USA
Sharib Gaffar
Affiliation:
Children’s Hospital of Orange County, Orange, CA92868, USA
Anthony C. Chang*
Affiliation:
Children’s Hospital of Orange County, Orange, CA92868, USA
*
Author for correspondence: Anthony C. Chang, CHOC Medical Intelligence and Innovation Institute (MI3), 1120 W. La Veta Ave., Suite 860, Orange, CA, USA. Tel: +1 425-877-9225. E-mail: [email protected]
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Abstract

The combination of pediatric cardiology being both a perceptual and a cognitive subspecialty demands a complex decision-making model which makes artificial intelligence a particularly attractive technology with great potential. The prototypical artificial intelligence system would autonomously impute patient data into a collaborative database that stores, syncs, interprets and ultimately classifies the patient’s profile to specific disease phenotypes to compare against a large aggregate of shared peer health data and outcomes, the current medical body of literature and ongoing trials to offer morbidity and mortality prediction, drug therapy options targeted to each patient’s genetic profile, tailored surgical plans and recommendations for timing of sequential imaging. The focus of this review paper is to offer a primer on artificial intelligence and paediatric cardiology by briefly discussing the history of artificial intelligence in medicine, modern and future applications in adult and paediatric cardiology across selected concentrations, and current barriers to implementation of these technologies.

Keywords

Cardiologypaediatricsartificial intelligence
Type
Review Article
Information
Cardiology in the Young , Volume 30 , Issue 7 , July 2020 , pp. 934 - 945
Copyright
© The Author(s), 2020. Published by Cambridge University Press

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