Anwendungen der künstlichen Intelligenz zur Automatisierung in der Gynäkologie und Geburtshilfe - eine Standortbestimmung

Translated title of the contribution: The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics - An Assessment of the State of Play

Jan Weichert*, Amrei Welp, Jann Lennard Scharf, Christoph Dracopoulos, Wolf Henning Becker, Michael Gembicki

*Corresponding author for this work
7 Citations (Scopus)

Abstract

The long-awaited progress in digitalisation is generating huge amounts of medical data every day, and manual analysis and targeted, patient-oriented evaluation of this data is becoming increasingly difficult or even infeasible. This state of affairs and the associated, increasingly complex requirements for individualised precision medicine underline the need for modern software solutions and algorithms across the entire healthcare system. The utilisation of state-of-the-art equipment and techniques in almost all areas of medicine over the past few years has now indeed enabled automation processes to enter - at least in part - into routine clinical practice. Such systems utilise a wide variety of artificial intelligence (AI) techniques, the majority of which have been developed to optimise medical image reconstruction, noise reduction, quality assurance, triage, segmentation, computer-aided detection and classification and, as an emerging field of research, radiogenomics. Tasks handled by AI are completed significantly faster and more precisely, clearly demonstrated by now in the annual findings of the ImageNet Large-Scale Visual Recognition Challenge (ILSVCR), first conducted in 2015, with error rates well below those of humans. This review article will discuss the potential capabilities and currently available applications of AI in gynaecological-obstetric diagnostics. The article will focus, in particular, on automated techniques in prenatal sonographic diagnostics.

Translated title of the contributionThe Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics - An Assessment of the State of Play
Original languageGerman
JournalGeburtshilfe und Frauenheilkunde
Volume81
Issue number11
Pages (from-to)1203-1216
Number of pages14
ISSN0016-5751
DOIs
Publication statusPublished - 22.04.2021

Research Areas and Centers

  • Centers: Center for Artificial Intelligence Luebeck (ZKIL)
  • Academic Focus: Biomedical Engineering

DFG Research Classification Scheme

  • 205-21 Gynaecology and Obstetrics

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