The present study reviews the publications that examine the application of machine learning
(ML) approaches in occupational accident analysis. The review process includes four …

Construction accidents can easily cause massive casualties and property losses. This
research uses machine learning technique to analyze 16 critical factors and assess the …

Although, the usefulness of the machine learning (ML) technique in predicting future
outcomes has been established in different domains of applications (eg, heath care), its …

The development of intelligence and informatization is the inevitable trend of safety
production in coal enterprises. Data mining technology plays an important role in promoting …

Fall or tumble is one of the most common accidents in bridge construction. Failing to
implement safety management and training effectively may result in serious occupational …

There are four primary accident types at steel building construction (SC) projects: falls
(tumbles), object falls, object collapse, and electrocution. Several systematic safety risk …

Mining is an economic sector with a high number of accidents. Mines are hazardous places
and workers can suffer a wide variety of injuries. Utilizing a database composed of almost …

Although machine learning methods have been used as an outcome prediction tool in many
fields, their utilization in predicting incident outcome in occupational safety is relatively new …

Abstract Slip-trip-fall (STF) accident is one of the leading causes of injuries. Therefore,
prediction of STF is necessary prior to its occurrence at workplaces. Although there exist a …

This article analyses, using Bayesian networks, the circumstances surrounding workplace
tasks performed using auxiliary equipment (ladders, scaffolding, etc.) that may result in falls …