You Only Look Once (YOLO) Based Machine Learning Algorithm for Real-Time Detection of Loop-Mediated Isothermal Amplification (LAMP) Diagnostics

Abstract

Loop-mediated isothermal amplification (LAMP) is a widely used rapid and affordable molecular DNA amplification method with minimal resource requirements. However, visual interpretation of results is subjective and prone to errors, leading to potential false-positive and negative results. To address this limitation, a machine-learning approach is proposed for automated LAMP classification based on digital images. The approach utilizes You Only Look Once (YOLOv8), a fast and robust object detection algorithm to locate and classify tubes within LAMP images, enabling automated categorization as positive or negative. The trained model achieved a high overall accuracy of 95.5% in classifying LAMP images into positive or negative. Additionally, the approach had a 98.0% precision and 92.7% recall for positive cases and 93.4% precision and 98.2% recall for negative cases, demonstrating its potential for real-time LAMP diagnosis and enhanced assay performance. This project demonstrated the platforms suitability for real-time testing, offering an easy operation and rapid results.