Microfluidic surface-enhanced Raman spectroscopy aided by artificial intelligence for biosensing

The integration of microfluidics, surface-enhanced Raman spectroscopy (SERS), and artificial intelligence (AI) is revolutionizing chemical and biomedical sensing. Microfluidic systems enable precise fluid control at the microscale, while SERS offers ultrasensitive, label-free molecular detection. Combining AI with microfluidic SERS enhances data processing, feature extraction, and automated decision-making, enabling efficient and intelligent diagnostics and analysis. This review highlights recent advances in AI-driven microfluidic SERS for biomedical detection and analysis, environmental monitoring, and chemical analysis. Key developments include improved detection accuracy, real-time classification, and high-throughput analysis. However, challenges such as data interpretability, computational complexity, and seamless integration must be addressed. Future research directions call for explainable AI, lightweight machine learning models, and privacy-preserving techniques to support broader adoption and safeguard sensitive information. By leveraging these technologies, researchers can develop innovative platforms for real-time sensing and analysis, ultimately advancing applications across healthcare, environmental science, and other interdisciplinary domains.