Artificial Intelligence in Biomedical Engineering: Current Advances and Future Perspectives in the United States

Abstract

Over the past few years, Artificial Intelligence (AI) has been a game-changer in biomedical engineering, transforming the design, validation and deployment of diagnostic, therapeutic, and monitoring systems across the U.S. healthcare landscape. In this review, recent progress in AI-powered medical imaging, wearable/implantable biosensing, drug discovery and precision medicine, and robotic and neural engineering is summarized, with a focus on the recent field of AI/machine-learning (ML) based medical devices and the regulatory landscape set by the U.S. Food and Drug Administration (FDA) for these devices. Based on peer-reviewed literature published primarily from 2023 to 2025, the review shows the shift of AI from experimental proof-of-concept to FDA regulated clinical products, records the rapid increase in FDA authorizations and outlines some ongoing issues around algorithmic bias, data governance, algorithm interpretability and demographic transparency. The review concludes with a discussion on future avenues for federated learning, foundation models, edge-AI wearables, and adaptive regulatory frameworks like Predetermined Change Control Plans (PCCPs) that will influence the next generation of biomedical AI systems in the United States.