Key points are not available for this paper at this time.
ABSTRACT Intelligent biosensors, empowered by machine learning and advanced functional materials, enable rapid and accurate disease diagnosis, personalized therapy, and continuous health monitoring without disrupting daily life. This integration facilitates a shift from traditional hospital‐centered healthcare to a more decentralized, patient‐centric model, where intelligent devices collect real‐time physiological data, perform deep analysis, and provide actionable insights for precise diagnosis and individualized treatment. Driven by advances in functional materials, interface engineering, and flexible manufacturing technologies, smart flexible sensing has achieved significant progress. In this review, we summarize recent developments spanning electrode material design and micro/nanostructure engineering, highlighting the progression from material design to device‐level integration. We further discuss machine learning strategies integrated into flexible diagnostic systems, highlighting the role of deep learning models in data interpretation, multimodal signal decoupling, and intelligent perception for adaptive human‒machine interaction. The review also outlines representative intelligent biosensing systems with emerging clinical applications in continuous monitoring and personalized healthcare, while discussing key challenges such as long‐term stability, biofouling, signal drift, device durability, and regulatory considerations, and provides perspectives for future intelligent healthcare technologies.
Xiao et al. (Fri,) studied this question.