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Erschienen in: best practice onkologie 5/2024

23.04.2024 | Künstliche Intelligenz | Topic

Künstliche Intelligenz in der Pathologie: Status quo und Zukunftsperspektiven

verfasst von: Dr. Sebastian Foersch, Stefan Schulz, M.Sc.

Erschienen in: best practice onkologie | Ausgabe 5/2024

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Zusammenfassung

Im Zuge einer zunehmenden Individualisierung onkologischer Diagnostik und Therapie stehen immer größere Datenbestände in Form von komplexen klinischen, molekularen, radiologischen und histopathologischen (Bild‑)Daten zur Verfügung. Zeitgleich erlauben Fortschritte auf technischer und algorithmischer Ebene im Bereich der künstlichen Intelligenz (KI) dieses medizinische „Big-Data-Reservoir“ diagnostisch sowie in der Vorhersage von Prognose und Therapieverläufen nutzbar zu machen. Trotz erster vielversprechender Anwendungen, die einen prinzipiellen Machbarkeitsnachweis liefern, steht eine flächendeckende Anwendung von KI-Verfahren in der alltäglichen pathologischen Praxis erst noch bevor. Voraussetzung hierfür ist eine Digitalisierung der Befundung, z. B. mithilfe des „whole-slide imaging“ (WSI). Kernpunkte für ein Gelingen der KI-Transformation der Pathologie werden voraussichtlich in einer Steigerung der Genauigkeit, Reproduzierbarkeit, Erklärbarkeit, Interpretierbarkeit und resultierenden Verlässlichkeit der KI-basierten Klassifizierungssysteme unter frühzeitigem Einbeziehen der menschlichen Patholog*innen bestehen. Diese Übersichtsarbeit informiert auf der Basis des aktuellen Forschungsstands über die momentane und zukünftige Bedeutung von Verfahren künstlicher Intelligenz für die histopathologische (Routine‑)Diagnostik.
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Metadaten
Titel
Künstliche Intelligenz in der Pathologie: Status quo und Zukunftsperspektiven
verfasst von
Dr. Sebastian Foersch
Stefan Schulz, M.Sc.
Publikationsdatum
23.04.2024
Verlag
Springer Medizin
Erschienen in
best practice onkologie / Ausgabe 5/2024
Print ISSN: 0946-4565
Elektronische ISSN: 1862-8559
DOI
https://doi.org/10.1007/s11654-024-00572-6

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