Machine learning-assisted electrochemical SERS for sensitive detection of multiple urinary proteins

Key Points

• Sensitive detection of multiple urinary proteins is achievable using machine learning-assisted SERS technology.
• The approach employs surface-enhanced Raman spectroscopy (SERS) to boost detection capabilities, showing enhanced specificity.
• Machine learning algorithms analyze spectral data, optimizing the identification of proteins in urine samples.
• This work highlights the potential for personalized medicine, indicating advances in non-invasive diagnostic methods.