Application Exploration of Artificial Intelligence Technology in the Innovative Development of Medical Equipment

Yahui Zhang

doi:10.62051/ijphmr.v6n6.02

Authors

Yahui Zhang

DOI:

https://doi.org/10.62051/ijphmr.v6n6.02

Keywords:

Artificial intelligence, Medical equipment, Medical imaging, Surgical robotics, Wearable devices, Federated learning, FDA, NMPA, Algorithm transparency

Abstract

The use of AI in medical devices is one of the greatest technological revolutions in modern medicine. This review focuses on the mechanisms and dimensions of AI application to medical equipment innovation in four domains, such as AI-enabled medical imaging devices, AI-assisted surgical robotics, AI-integrated wearable monitoring devices, and federated learning-based data infrastructure for equipment development. A review of regulatory data, clinical evidence and emerging technical literature traces the evolution of AI-enabled device authorisations – from 27 FDA-cleared devices in 2017 to 235 in 2024 (with more than 1,000 cumulative authorisations) – and discusses the technology-specific drivers of this growth. A technology innovation diffusion framework and the human-AI collaboration concept are used to contextualise the systemic implications of AI integration at the equipment level. We tackle and evaluate major issues, including the lack of transparency in algorithms, differences in regulations between the U.S. Food and Drug Administration and China’s National Medical Products Administration, restrictions on data privacy, algorithmic bias, and the development of governance frameworks. The assessment finishes with pragmatic thoughts on how to bridge the device-level AI performance with the system-level healthcare outcomes and on the development of internationally harmonised evaluation criteria for AI-enabled medical equipment.

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