The sustainable development of artificial intelligence (AI) systems in healthcare requires not only technological innovation but also a responsible and comprehensive regulatory framework. This chapter analyzes how current European and international regulatory mechanisms influence the development, implementation, and long-term sustainability of healthcare AI systems, with a particular focus on the field of radiology. The role of directives such as the AI Act, MDR/IVDR, GDPR, NIS2, and European Health Data Space (EHDS) is discussed, as well as the importance of ESG principles and post-market surveillance for AI life cycle management. Attention is also paid to international regulatory harmonization, adaptive approaches (e.g., PCCP), and the use of nonfinancial indicators. The chapter provides strategic recommendations to support sustainable, transparent, and equitable digitalization of healthcare. The aim is to show that regulation and sustainability are not opposites, but mutually reinforcing concepts that together shape a credible future for healthcare AI.

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Regulatory Issues in Sustainable Healthcare

  • Lukas Peter,
  • Petr Straka,
  • Aneta Kovarova,
  • Kamil Kuca,
  • Petra Maresova

摘要

The sustainable development of artificial intelligence (AI) systems in healthcare requires not only technological innovation but also a responsible and comprehensive regulatory framework. This chapter analyzes how current European and international regulatory mechanisms influence the development, implementation, and long-term sustainability of healthcare AI systems, with a particular focus on the field of radiology. The role of directives such as the AI Act, MDR/IVDR, GDPR, NIS2, and European Health Data Space (EHDS) is discussed, as well as the importance of ESG principles and post-market surveillance for AI life cycle management. Attention is also paid to international regulatory harmonization, adaptive approaches (e.g., PCCP), and the use of nonfinancial indicators. The chapter provides strategic recommendations to support sustainable, transparent, and equitable digitalization of healthcare. The aim is to show that regulation and sustainability are not opposites, but mutually reinforcing concepts that together shape a credible future for healthcare AI.