Auswirkung von Künstlicher Intelligenz auf den Beruf der MTR

Dieser Artikel befasst sich mit den Auswirkungen der Künstlichen Intelligenz (KI) auf den Beruf der Medizinischen Technologinnen und Technologen für Radiologie (MTR). Die KI könnte entlang des Patientenbehandlungspfades in sämtlichen Bereichen der Radiologie MTR unterstützen und entlasten. Durch KI könnte sich der MTR-Beruf in Tätigkeitsbereiche unterteilen, die sich in patientennahe und patientenferne Tätigkeiten gliedern. In Zukunft könnten MTR, die Expertise im Bereich von KI besitzen, supervisorische Tätigkeiten ausführen, während MTR, die sich nicht mit KI beschäftigen, patientennahe Tätigkeiten wie die Betreuung und Lagerung von Patienten durchführen. Es ist absehbar, dass KI in naher Zukunft einige Aufgaben der MTR übernehmen wird und in ferner Zukunft autonom Untersuchungen durchführen wird. Um den Beruf des MTR zukunftsfähig zu gestalten, sollten MTR eine Strategie entwickeln und aktiv an der Entwicklung mitwirken.

Abstract

This article explores the impact of artificial intelligence (AI) on radiology technology, focusing on the changing roles and responsibilities of radiology technologists due to technological advancements. The introduction of AI-driven diagnostic tools has improved the efficiency and precision of medical imaging, allowing radiology technologists to streamline their workflow. This article examines the relationship between radiology technologists and AI, highlighting the significance of skill adaptation and professional development. Additionally, it discusses the impact of AI on the job market for radiology technologists, exploring how automation may reshape the profession. The study emphasizes the importance of the human touch in patient care and the interpretative nuances that AI may struggle to comprehend. Radiology technologists play a crucial role in developing, validating, and optimizing AI algorithms to ensure they align seamlessly with the complexities of medical imaging. This article highlights the dynamic relationship between radiology technologists and artificial intelligence, emphasizing the symbiosis between human expertise and technological innovation. As artificial intelligence (AI) continues to advance, radiology technologists must adapt their skills to embrace the opportunities for improved efficiency, while maintaining a commitment to ethical practice and patient-centered care.

Schlüsselwörter

Künstliche Intelligenz - Maschinelles Lernen - Deep Learning - MTR - Zukunftsfähigkeit

Key word

Artificial intelligence - machine learning - deep learning - radiology technologist - future skills

• Literatur

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