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Artificial Intelligence in Pediatric Cardiology: Where Do We Stand in 2024?

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Date 2024 Aug 26
PMID 39184112
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References
1.
Corral-Acero J, Margara F, Marciniak M, Rodero C, Loncaric F, Feng Y . The 'Digital Twin' to enable the vision of precision cardiology. Eur Heart J. 2020; 41(48):4556-4564. PMC: 7774470. DOI: 10.1093/eurheartj/ehaa159. View

2.
Sachdeva S, Ramakrishnan S . Fetal cardiology in India - At the crossroads. Ann Pediatr Cardiol. 2023; 15(4):347-350. PMC: 10015389. DOI: 10.4103/apc.apc_156_22. View

3.
Gritti M, Alturki H, Farid P, Morgan C . Progression of an Artificial Intelligence Chatbot (ChatGPT) for Pediatric Cardiology Educational Knowledge Assessment. Pediatr Cardiol. 2024; 45(2):309-313. DOI: 10.1007/s00246-023-03385-6. View

4.
Van den Eynde J, Manlhiot C, Van De Bruaene A, Diller G, Frangi A, Budts W . Medicine-Based Evidence in Congenital Heart Disease: How Artificial Intelligence Can Guide Treatment Decisions for Individual Patients. Front Cardiovasc Med. 2021; 8:798215. PMC: 8674499. DOI: 10.3389/fcvm.2021.798215. View

5.
Olive M, Owens G . Current monitoring and innovative predictive modeling to improve care in the pediatric cardiac intensive care unit. Transl Pediatr. 2018; 7(2):120-128. PMC: 5938248. DOI: 10.21037/tp.2018.04.03. View