Machine Learning in Paediatric Cardiac Surgery: Ready for Prime Time? (Editorial)
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Marathe, Supreet P
Suna, Jessica
Venugopal, Prem
Chai, Kevin
Alphonso, Nelson
Queensland Paediatric Cardiac Research (QPCR) Group
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Abstract
Machine learning (ML) is a branch of artificial intelligence which involves ‘learning’ the complex relationships between predictors and outcomes. Despite wide availability, these techniques have been rarely implemented into everyday clinical practice. The use of ML in paediatric cardiac surgery is even rarer. The time has come to employ ML to develop risk adjustment models for patient prognosis and benchmarking as a natural starting point for real-time personalised risk prediction in paediatric cardiac surgery.
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Heart, Lung and Circulation
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31
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5
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Subject
Paediatrics
Machine learning
Cardiovascular medicine and haematology
Surgery
Health services and systems
Public health
Science & Technology
Life Sciences & Biomedicine
Cardiac & Cardiovascular Systems
Cardiovascular System & Cardiology
Machine learning
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Citation
Betts, KS; Marathe, SP; Suna, J; Venugopal, P; Chai, K; Alphonso, N; Queensland Paediatric Cardiac Research (QPCR) Group, Machine Learning in Paediatric Cardiac Surgery: Ready for Prime Time? (Editorial), Heart, Lung and Circulation, 2022, 31 (5), pp. 613-615