Machine learning-assisted image-based optical devices for health monitoring and food safety

The advent of artificial intelligence has highly impacted the process of image processing and pattern recognition, hence influencing biomedical researchers to implement machine learning (ML)-assisted image-based analysis in the development of optical sensors. Optical detection devices provide the optimal platforms for image-based analysis as they exhibit signals that can be captured by cameras. Relying on ML for pattern recognition from the captured images can highly enhance the detection accuracy and pave the way toward developing point-ofcare testing. In this review, we have aimed to present an overview based on image processing and how ML can be implemented in pattern recognition from images. Recent publications on the development of optical detection devices relying on ML-assisted image analysis in various fields of biomedical analysis have then been reviewed.