Aktuelle Aspekte zur künstlichen Intelligenz in der gynäkologischen Diagnostik

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

doi:10.1007/s00129-022-04993-8

Aktuelle Aspekte zur künstlichen Intelligenz in der gynäkologischen Diagnostik

Translated title of the contribution: Current aspects of artificial intelligence in gynecological diagnostics

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

^*Corresponding author for this work

Department of Gynecology and Obstetrics

Abstract

Artificial intelligence (AI) applications have rapidly increased in medicine. In contrast to obstetrics and prenatal diagnostics, AI in gynecology has not yet been applied in clinical practice. However, AI can aid in preoperative differentiation between benign and malignant lesions of the ovaries, in diagnosis of endometriosis, and assist in the differentiation between leiomyomas and leiomyosarcomas or the classification of Müller duct anomalies. In gynecologic oncology, AI has made tremendous progress by improving cervical cancer detection, ovarian cancer imaging, and uterine cancer diagnosis. This review article examines current aspects of AI algorithms in gynecological diagnostics.

Translated title of the contribution	Current aspects of artificial intelligence in gynecological diagnostics
Original language	German
Journal	Gynakologie
Volume	55
Issue number	10
Pages (from-to)	759-770
Number of pages	12
ISSN	2731-7102
DOIs	https://doi.org/10.1007/s00129-022-04993-8
Publication status	Published - 10.2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 5 Gender Equality
SDG 9 Industry, Innovation, and Infrastructure
SDG 10 Reduced Inequalities

Research Areas and Centers

Centers: Center for Artificial Intelligence Luebeck (ZKIL)

DFG Research Classification Scheme

2.22-21 Gynaecology and Obstetrics
2.22-07 Medical Informatics and Medical Bioinformatics

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10.1007/s00129-022-04993-8

Cite this

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title = "Aktuelle Aspekte zur k{\"u}nstlichen Intelligenz in der gyn{\"a}kologischen Diagnostik",

abstract = "Artificial intelligence (AI) applications have rapidly increased in medicine. In contrast to obstetrics and prenatal diagnostics, AI in gynecology has not yet been applied in clinical practice. However, AI can aid in preoperative differentiation between benign and malignant lesions of the ovaries, in diagnosis of endometriosis, and assist in the differentiation between leiomyomas and leiomyosarcomas or the classification of M{\"u}ller duct anomalies. In gynecologic oncology, AI has made tremendous progress by improving cervical cancer detection, ovarian cancer imaging, and uterine cancer diagnosis. This review article examines current aspects of AI algorithms in gynecological diagnostics.",

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

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive licence to Springer Medizin Verlag GmbH, ein Teil von Springer Nature.",

year = "2022",

month = oct,

doi = "10.1007/s00129-022-04993-8",

language = "Deutsch",

volume = "55",

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T1 - Aktuelle Aspekte zur künstlichen Intelligenz in der gynäkologischen Diagnostik

AU - Scharf, Jann Lennard

AU - Dracopoulos, Christoph

AU - Gembicki, Michael

AU - Welp, Amrei

AU - Weichert, Jan

PY - 2022/10

Y1 - 2022/10

N2 - Artificial intelligence (AI) applications have rapidly increased in medicine. In contrast to obstetrics and prenatal diagnostics, AI in gynecology has not yet been applied in clinical practice. However, AI can aid in preoperative differentiation between benign and malignant lesions of the ovaries, in diagnosis of endometriosis, and assist in the differentiation between leiomyomas and leiomyosarcomas or the classification of Müller duct anomalies. In gynecologic oncology, AI has made tremendous progress by improving cervical cancer detection, ovarian cancer imaging, and uterine cancer diagnosis. This review article examines current aspects of AI algorithms in gynecological diagnostics.

AB - Artificial intelligence (AI) applications have rapidly increased in medicine. In contrast to obstetrics and prenatal diagnostics, AI in gynecology has not yet been applied in clinical practice. However, AI can aid in preoperative differentiation between benign and malignant lesions of the ovaries, in diagnosis of endometriosis, and assist in the differentiation between leiomyomas and leiomyosarcomas or the classification of Müller duct anomalies. In gynecologic oncology, AI has made tremendous progress by improving cervical cancer detection, ovarian cancer imaging, and uterine cancer diagnosis. This review article examines current aspects of AI algorithms in gynecological diagnostics.

UR - https://www.scopus.com/pages/publications/85150439669

U2 - 10.1007/s00129-022-04993-8

DO - 10.1007/s00129-022-04993-8

M3 - Übersichtsarbeiten

AN - SCOPUS:85150439669

SN - 2731-7102

VL - 55

SP - 759

EP - 770

JO - Gynakologie

JF - Gynakologie

IS - 10

ER -

Aktuelle Aspekte zur künstlichen Intelligenz in der gynäkologischen Diagnostik

Abstract

UN SDGs

Research Areas and Centers

DFG Research Classification Scheme

Access to Document

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