Kunstig intelligens og føtalmedicinsk ultralydskanning

Caroline Taksøe-Vester; Zahra Bashir; Emilie Pi Fogtmann Sejer; Mary Le Ngo; Lars Henning Pedersen; Mikkel Friis; Olav Bjørn Petersen; Aasa Feragen; Mads Nielsen; Anders Nymark Christensen; Martin G Tolsgaard

doi:10.61409/V10240748

Kunstig intelligens og føtalmedicinsk ultralydskanning

Translated title of the contribution: Artificial intelligence and ultrasound in fetal medicine

Caroline Taksøe-Vester, Zahra Bashir, Emilie Pi Fogtmann Sejer, Mary Le Ngo, Lars Henning Pedersen, Mikkel Friis, Olav Bjørn Petersen, Aasa Feragen, Mads Nielsen, Anders Nymark Christensen, Martin G Tolsgaard

1 Citation (Scopus)

Abstract

Ultrasound is essential in fetal medicine for diagnosing and monitoring, but it requires extensive training. Artificial intelligence (AI) shows a great promise in enhancing the clinical training and practice, by improving workflow and standardising diagnostics. Despite its potential, AI's limitations and regulatory challenges must be addressed before full integration. Research should focus on implementation to achieve successful use in clinical practice. Ultimately, AI is expected to support clinicians rather than replace them, improving diagnostic accuracy and efficiency in fetal medicine.

Translated title of the contribution	Artificial intelligence and ultrasound in fetal medicine
Original language	Danish
Article number	V10240748
Journal	Ugeskrift for Laeger
Volume	187
Issue number	18
ISSN	0041-5782
DOIs	https://doi.org/10.61409/V10240748
Publication status	Published - 28 Apr 2025

Access to Document

10.61409/V10240748Licence: CC BY-NC-ND

Cite this

@article{8580576c5fbf40da9f30480f4c0d8540,

title = "Kunstig intelligens og f{\o}talmedicinsk ultralydskanning",

abstract = "Ultrasound is essential in fetal medicine for diagnosing and monitoring, but it requires extensive training. Artificial intelligence (AI) shows a great promise in enhancing the clinical training and practice, by improving workflow and standardising diagnostics. Despite its potential, AI's limitations and regulatory challenges must be addressed before full integration. Research should focus on implementation to achieve successful use in clinical practice. Ultimately, AI is expected to support clinicians rather than replace them, improving diagnostic accuracy and efficiency in fetal medicine.",

keywords = "Humans, Artificial Intelligence, Ultrasonography, Prenatal/methods, Pregnancy, Female",

author = "Caroline Taks{\o}e-Vester and Zahra Bashir and Sejer, \{Emilie Pi Fogtmann\} and Ngo, \{Mary Le\} and Pedersen, \{Lars Henning\} and Mikkel Friis and Petersen, \{Olav Bj{\o}rn\} and Aasa Feragen and Mads Nielsen and Christensen, \{Anders Nymark\} and Tolsgaard, \{Martin G\}",

note = "Published under Open Access CC-BY-NC-BD 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/.",

year = "2025",

month = apr,

day = "28",

doi = "10.61409/V10240748",

language = "Dansk",

volume = "187",

journal = "Ugeskrift for Laeger",

issn = "0041-5782",

publisher = "Almindelige Danske Laegeforening",

number = "18",

}

TY - JOUR

T1 - Kunstig intelligens og føtalmedicinsk ultralydskanning

AU - Taksøe-Vester, Caroline

AU - Bashir, Zahra

AU - Sejer, Emilie Pi Fogtmann

AU - Ngo, Mary Le

AU - Pedersen, Lars Henning

AU - Friis, Mikkel

AU - Petersen, Olav Bjørn

AU - Feragen, Aasa

AU - Nielsen, Mads

AU - Christensen, Anders Nymark

AU - Tolsgaard, Martin G

N1 - Published under Open Access CC-BY-NC-BD 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/.

PY - 2025/4/28

Y1 - 2025/4/28

N2 - Ultrasound is essential in fetal medicine for diagnosing and monitoring, but it requires extensive training. Artificial intelligence (AI) shows a great promise in enhancing the clinical training and practice, by improving workflow and standardising diagnostics. Despite its potential, AI's limitations and regulatory challenges must be addressed before full integration. Research should focus on implementation to achieve successful use in clinical practice. Ultimately, AI is expected to support clinicians rather than replace them, improving diagnostic accuracy and efficiency in fetal medicine.

AB - Ultrasound is essential in fetal medicine for diagnosing and monitoring, but it requires extensive training. Artificial intelligence (AI) shows a great promise in enhancing the clinical training and practice, by improving workflow and standardising diagnostics. Despite its potential, AI's limitations and regulatory challenges must be addressed before full integration. Research should focus on implementation to achieve successful use in clinical practice. Ultimately, AI is expected to support clinicians rather than replace them, improving diagnostic accuracy and efficiency in fetal medicine.

KW - Humans

KW - Artificial Intelligence

KW - Ultrasonography, Prenatal/methods

KW - Pregnancy

KW - Female

UR - https://www.scopus.com/pages/publications/105005377863

U2 - 10.61409/V10240748

DO - 10.61409/V10240748

M3 - Review

C2 - 40358082

SN - 0041-5782

VL - 187

JO - Ugeskrift for Laeger

JF - Ugeskrift for Laeger

IS - 18

M1 - V10240748

ER -

Kunstig intelligens og føtalmedicinsk ultralydskanning

Abstract

Access to Document

Other files and links

Fingerprint

Cite this