Dual stimulus-responsive core-satellite SERS nanoprobes for reactive oxygen species sensing during autophagy.

Abstract Surface‐enhanced Raman spectroscopy (SERS) has shown strength in non‐invasive, rapid, trace analysis and has been used in many fields in medicine. Machine learning (ML) is an algorithm that can imitate human learning styles and structure existing content with the knowledge to effectively improve learning efficiency. Integrating SERS and ML can have a promising future in the medical field. In this review, we summarize the applications of SERS combined with ML in recent years, such as the recognition of biological molecules, rapid diagnosis of diseases, developing of new immunoassay techniques, and enhancing SERS capabilities in semi‐quantitative measurements. Ultimately, the possible opportunities and challenges of combining SERS with ML are addressed.

Zhengsheng Mao

Papers

Crown monitoring: Trace the dynamic changes of caspase-3 and H2O2 in real-time imaging based on FRET/SERS.