Künstliche Intelligenz in der pränatalen kardialen Diagnostik

Jan Weichert; Amrei Welp; Jann Lennard Scharf; Christoph Dracopoulos; Achim Rody; Michael Gembicki

doi:10.1007/s00129-021-04890-6

Künstliche Intelligenz in der pränatalen kardialen Diagnostik

Translated title of the contribution: Artificial intelligence in prenatal cardiac diagnostics

Jan Weichert^*, Amrei Welp, Jann Lennard Scharf, Christoph Dracopoulos, Achim Rody, Michael Gembicki

^*Corresponding author for this work

Abstract

The prenatal detection rates of fetal heart defects have remained low despite the implementation of national and international screening programs. The detection rates in the low-risk population range from 22.5% to 52.8%. Promising approaches for improved detection rates could include automated applications of artificial intelligence (AI). With reference to novel and already established AI solutions from adult cardiology, this review discusses the possibilities and limitations of AI algorithms for fetal echocardiography.

Translated title of the contribution	Artificial intelligence in prenatal cardiac diagnostics
Original language	German
Journal	Gynakologe
Volume	55
Issue number	1
Pages (from-to)	22-31
Number of pages	10
ISSN	0017-5994
DOIs	https://doi.org/10.1007/s00129-021-04890-6
Publication status	Published - 01.2022

Research Areas and Centers

Centers: Center for Artificial Intelligence Luebeck (ZKIL)

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abstract = "The prenatal detection rates of fetal heart defects have remained low despite the implementation of national and international screening programs. The detection rates in the low-risk population range from 22.5% to 52.8%. Promising approaches for improved detection rates could include automated applications of artificial intelligence (AI). With reference to novel and already established AI solutions from adult cardiology, this review discusses the possibilities and limitations of AI algorithms for fetal echocardiography.",

author = "Jan Weichert and Amrei Welp and Scharf, {Jann Lennard} and Christoph Dracopoulos and Achim Rody and Michael Gembicki",

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AU - Dracopoulos, Christoph

AU - Rody, Achim

AU - Gembicki, Michael

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AB - The prenatal detection rates of fetal heart defects have remained low despite the implementation of national and international screening programs. The detection rates in the low-risk population range from 22.5% to 52.8%. Promising approaches for improved detection rates could include automated applications of artificial intelligence (AI). With reference to novel and already established AI solutions from adult cardiology, this review discusses the possibilities and limitations of AI algorithms for fetal echocardiography.

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Künstliche Intelligenz in der pränatalen kardialen Diagnostik

Abstract

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