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<p>Orthopedics, as an imaging-intensive and data-rich specialty, offers significant potential for the application of artificial intelligence (AI) in areas such as diagnostics, therapy, and rehabilitation. Numerous AI applications have already been experimentally tested and show promising results. Nevertheless, the routine use of AI in clinical practice remains the exception. A&#xa0;crucial prerequisite for its successful implementation in real-world clinical settings is the development of strategic, technical, and organizational foundations, commonly referred to as AI readiness. This particularly includes building central, interoperable data platforms with clear governance structures that harmonize clinical data from various source systems and ensure its accessibility. International examples demonstrate that such infrastructures are technically feasible. However, within the German system landscape, these initiatives still require clear overall strategic planning, sufficient human and technical resources, interdisciplinary expertise, and an open, innovation-ready corporate culture. A high level of AI readiness is a prerequisite for the routine clinical use of AI in orthopedics.</p>

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KI-Readiness als Voraussetzung für den klinischen Einsatz von künstlicher Intelligenz in der Orthopädie

  • 期刊论文

  • 发表日期：

    2025年9月2日

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  • Laura J. Amenda,
  • Christina Valle,
  • Rüdiger von Eisenhart-Rothe,
  • Martin Boeker,
  • Florian Hinterwimmer

摘要

Orthopedics, as an imaging-intensive and data-rich specialty, offers significant potential for the application of artificial intelligence (AI) in areas such as diagnostics, therapy, and rehabilitation. Numerous AI applications have already been experimentally tested and show promising results. Nevertheless, the routine use of AI in clinical practice remains the exception. A crucial prerequisite for its successful implementation in real-world clinical settings is the development of strategic, technical, and organizational foundations, commonly referred to as AI readiness. This particularly includes building central, interoperable data platforms with clear governance structures that harmonize clinical data from various source systems and ensure its accessibility. International examples demonstrate that such infrastructures are technically feasible. However, within the German system landscape, these initiatives still require clear overall strategic planning, sufficient human and technical resources, interdisciplinary expertise, and an open, innovation-ready corporate culture. A high level of AI readiness is a prerequisite for the routine clinical use of AI in orthopedics.