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Künstliche Intelligenz in der Medizin

Chancen und Anforderungen für einen erfolgreichen und nachhaltigen Einsatz im Gesundheitswesen

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Zusammenfassung

Um aus großen Datenmengen Wissen mit einem echten Mehrwert zu generieren ist es notwendig aus der sich anbahnenden Big Data Situation in Krankenhäusern eine Smart Data Umgebung zu schaffen. Erst hierdurch werden Daten für innovative Algorithmen aus dem Bereich der Künstlichen Intelligenz (KI) verwertbar gemacht. Der Einsatz von KI-Methoden in der Medizin erfordert technische, organisatorische und medikolegale Aspekte. Das vorliegende Kapitel führt hierzu in den Begriff der Künstlichen Intelligenz (KI) ein, nennt hierzu beispielhafte Anwendungen in der Medizin und geht insbesondere auf technische Aspekte wie Datengenerierung, Datenanalyse und Regulatorik ein. Dies ermöglicht die Identifikation bekannter und wiederkehrender Herausforderungen sowie die Planung und Umsetzung von Lösungen in diesem noch jungen aber rasant wachsenden Bereich.

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Author information

Authors and Affiliations

  1. Universität Münster, Münster, Deutschland

    Julian Varghese

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  1. Julian Varghese
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Editors and Affiliations

  1. DMI GmbH & Co. KG, Münster, Deutschland

    Viola Henke

  2. FOM Hochschule für Oekonomie & Management, Essen, Deutschland

    Gregor Hülsken

  3. Asklepios Kliniken GmbH & Co. KGaA, Hamburg, Deutschland

    Henning Schneider

  4. Institut für Medizinische Informatik, Universität Münster, Münster, Deutschland

    Julian Varghese

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© 2024 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

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Varghese, J. (2024). Künstliche Intelligenz in der Medizin. In: Henke, V., Hülsken, G., Schneider, H., Varghese, J. (eds) Health Data Management. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-43236-2_50

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  • DOI: https://doi.org/10.1007/978-3-658-43236-2_50

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