Machine learning algorithms for surface plasmon resonance bio-detection applications, A short review

Surface plasmon resonance (SPR) sensors have many applications in detecting toxic gases, water pollutants, and biomarkers of many diseases. Surface plasmon resonance sensors are a good candidate for future sensing platforms due to their high sensitivity and fine resolution. However, the challenges of high cost, cross-sensitivity, and large amount of generated data need to be addressed to unlock surface plasmon resonance potential. Machine learning (ML) algorithms can address these challenges. In this short review, recent studies integrating the algorithms of Artificial Intelligence (AI) and Machine Learning (ML) with (SPR) sensing mechanisms for bio-detection applications are presented here. This short review shows how the integrated approach can help mitigate some of the challenges faced by traditional SPR sensing.