Automated monitoring in In vitro diagnostics: enhancing precision with machine learning and computer vision

In Vitro Diagnostics (IVD) is an application belonging to the fields of science and technology, able to extract from human biological sample reliable information which are related to the diagnosis of the state of health of an individual. It is currently undergoing a significant evolution due to technological innovation and process automation. Given the increasing prevalence of automation in IVD, it is crucial to ensure that automated processes and devices are constantly monitored to minimize false negatives. This study introduces an automated monitoring system that utilizes Machine Learning and Computer Vision techniques to analyze IVD device analysis processes in real-time.