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CC BY-NC-ND 4.0 · Klin Monbl Augenheilkd 2024; 241(09): 1023-1031
DOI: 10.1055/a-2378-6138
Übersicht

Rolle der künstlichen Intelligenz bei verschiedenen retinalen Erkrankungen

Article in several languages: deutsch | English
Julia Mai
Universitätsklinik für Augenheilkunde und Optometrie, Medizinische Universität Wien, Österreich
,
Ursula Schmidt-Erfurth
Universitätsklinik für Augenheilkunde und Optometrie, Medizinische Universität Wien, Österreich
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Zusammenfassung

Die künstliche Intelligenz (KI) hat bereits Einzug in die Augenheilkunde gefunden durch erste zugelassene Algorithmen, die in der Praxis angewendet werden können. Als ein relevantes Anwendungsgebiet der KI erweisen sich insbesondere retinale Erkrankungen, da sie die Hauptursache einer Erblindung darstellen und die Zahl an Patienten, die an einer Netzhauterkrankung leiden, stetig zunimmt. Gleichzeitig werden durch die regelmäßige standardisierte und gut reproduzierbare Bildgebung mittels hochauflösender Modalitäten immense Datenmengen generiert, die von menschlichen Experten kaum zu verarbeiten sind. Außerdem erfährt die Augenheilkunde stetig neue Entwicklungen und Durchbrüche, die einer Reevaluierung des Patientenmanagements in der klinischen Routine bedürfen. Die KI ist in der Lage, diese Datenmengen effizient und objektiv zu analysieren und zusätzlich durch die Identifizierung relevanter Biomarker neue Einblicke in Krankheitsprozesse sowie Therapiemechanismen zu liefern. Die KI kann maßgeblich zum Screening, zur Klassifizierung sowie zur Prognose von unterschiedlichen Netzhauterkrankungen beitragen. Anwendungsfreundliche Auswertungstools (Clinical Decision Support Systems) für den klinischen Alltag sind bereits erhältlich, die Praxis und Gesundheitssystem durch effizientere Nutzung kosten- und zeitintensiver Ressourcen erheblich entlasten.

Schlüsselwörter

Netzhaut - optische Kohärenztomografie - künstliche Intelligenz - retinale Bildgebung


Publication History

Received: 24 April 2024

Accepted: 30 July 2024

Article published online:
16 September 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commecial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

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