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

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

^*Korrespondierende/r Autor/-in für diese Arbeit

Klinik für Frauenheilkunde und Geburtshilfe

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.

Titel in Übersetzung	Artificial intelligence in prenatal cardiac diagnostics
Originalsprache	Deutsch
Zeitschrift	Gynakologe
Jahrgang	55
Ausgabenummer	1
Seiten (von - bis)	22-31
Seitenumfang	10
ISSN	0017-5994
DOIs	https://doi.org/10.1007/s00129-021-04890-6
Publikationsstatus	Veröffentlicht - 01.2022

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10.1007/s00129-021-04890-6

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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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doi = "10.1007/s00129-021-04890-6",

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AU - Weichert, Jan

AU - Welp, Amrei

AU - Scharf, Jann Lennard

AU - Dracopoulos, Christoph

AU - Rody, Achim

AU - Gembicki, Michael

PY - 2022/1

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N2 - 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.

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

Strategische Forschungsbereiche und Zentren

UN SDGs

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