The Holy Grail of obstetric ultrasound: can artificial intelligence detect hard-to-identify fetal cardiac anomalies?
- PMID: 38949769
- DOI: 10.1002/uog.27703
The Holy Grail of obstetric ultrasound: can artificial intelligence detect hard-to-identify fetal cardiac anomalies?
Comment on
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Interaction between clinicians and artificial intelligence to detect fetal atrioventricular septal defects on ultrasound: how can we optimize collaborative performance?Ultrasound Obstet Gynecol. 2024 Jul;64(1):28-35. doi: 10.1002/uog.27577. Epub 2024 Jun 3. Ultrasound Obstet Gynecol. 2024. PMID: 38197584
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Role of artificial-intelligence-assisted automated cardiac biometrics in prenatal screening for coarctation of aorta.Ultrasound Obstet Gynecol. 2024 Jul;64(1):36-43. doi: 10.1002/uog.27608. Epub 2024 Jun 3. Ultrasound Obstet Gynecol. 2024. PMID: 38339776
References
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- Chu C, Yan Y, Ren Y, Li X, Gui Y. Prenatal diagnosis of congenital heart diseases by fetal echocardiography in second trimester: a Chinese multicenter study. Acta Obstet Gynecol Scand. 2017;96:454‐463.
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- Karim JN, Bradburn E, Roberts N, Papageorghiou AT, ACCEPTS study. First‐trimester ultrasound detection of fetal heart anomalies: systematic review and meta‐analysis. Ultrasound Obstet Gynecol. 2022;59:11‐25.
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- Bottelli L, Franze V, Tuo G, Buffelli F, Paladini D. Prenatal detection of congenital heart disease at 12‐13 gestational weeks: detailed analysis of false‐negative cases. Ultrasound Obstet Gynecol. 2023;61:577‐586.
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