Pregnant women are advised to take a fetal screening ultrasound during the second trimester to help diagnose congenital heart disease. However, interpreting the thousands of image frames is still complex, making the fetal diagnosis a challenge. This episode presents two studies that exemplify the use of artificial intelligence (AI) in cardiology, detecting congenital heart disease using imaging approaches during the prenatal period.

References

1. Arnaout R, Curran L, Zhao Y, Levine JC, Chinn E, Moon-Grady AJ. An ensemble of neural networks provides expert-level prenatal detection of complex congenital heart disease. Nat Med. [Internet]. 2021. (Accessed on May 31, 2022); 27(5):882–891. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380434/ Author manuscript; available in PMC 2021 August 2.
2. Rizzo G, Pietrolucci ME, Capponi A, Mappa I. Exploring the role of artificial intelligence in the study of fetal heart. Int J Cardiovasc Imaging. [Internet]. 2021. (Accessed on May 31, 2022);38:1017–1019. Available at: https://doi.org/10.1007/s10554-022-02588-x
3. Truong VT, Nguyen BP, Nguyen-Vo TH. Application of machine learning in screening for congenital heart diseases using fetal echocardiography. Int J Cardiovasc Imaging. [Internet]. 2021. (Accessed on May 31, 2022);38:1007–1015. Available at: 3. https://doi.org/10.1007/s10554-022-02566-3

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