… safety management based on machine learning that aims to address the shortcomings of
traditional laboratory safety … In this paper, the safety data of laboratories in Southwest University …

… for achieving effective safety management. Emerging as an important component of proactive
safety management, leading indicators are used to assess and control safety performance. …

… safety analysis and management through machine learning. … of construction safety
management using machine learning [… safety management based upon machine learning, in order …

… In this section, we will list typical machine learning techniques used in the safety management
of NPPs, such as the well-known Artificial Neural Network (ANN), Support Vector Machine …

… As application of ML in construction safety management, especially in the area of safety
leading indicator, is still relatively new, this study provides foundation for future ML applications …

… in machine learning and computer vision are now enabling the development of sensor-based
safety management … opportunities for improving safety management. While considerable …

… feasibility of using signal processing and machine learning techniques to understand teamwork
and behaviour related to healthcare management and patient safety, and to contribute to …

… on Machine Learning (ML) for reliability engineering and safety … Machine learning pervades
an increasing number of fields, … Roughly speaking, “machine learning [is] a set of methods …

… Over the past few years, researchers have been formulating various machine learning (ML)
applications for various fields [14,15,16,17]. Prime ML applications in SHM and JSM include …

… Safety performance functions (SPFs) are the key regression tools in the road safety management
… Although regression-based SPFs have been proven to be reliable tools for road safety …