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Abstract Extracellular vesicles (EVs) are promising non-invasive biomarkers for early cancer detection, yet clinical translation is limited by membrane fouling during isolation and vesicle aggregation during single-vesicle imaging. Here, iEVIP (intelligent extracellular vesicle isolation and profiling), an integrated dual-inspired platform, combines intelligent pulsatile filtration, blood-smear-inspired nanoscale organization and machine-learning-based classification.
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