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Workers’ health and safety are a major concern in society, since work accidents have a major impact on productivity and economy. In Brazil, the accidents are officially reported through Work Accident Communication and they are available to the public. Thus, this study analyzed a balanced dataset containing 1,206 records of deaths caused by work accidents related to the transport sector. Its aim was analyzing how the deaths in the transport sector are related with the other work accident factors. To achieve this goal, twelve performance data mining techniques are compared, through five performance metrics, regarding the predictive capacity of the occurrence of deaths caused by work accidents. In this context, the XGBoost and Naïve Bayes algorithms showed the best predictive capacity. The explanatory analysis indicates that work accidents followed by death in road transport are predictable due to the severity of the injuries and vital parts of the body are affected.

Trucks are attached to many industries in different sectors like an industrial equipment. For this reason, select a truck without consider the best attributes for the company could cause futures problems. Therefore, this article presents a systematic review of studies that approach quantitative and qualitative decision-making support methods and attributes that help on collecting of precision data. Thus, a framework was created to describe the factors and characteristics of studies, like the application types, hybrid models, sources and data validation. As result, 11 articles were selected from 893, published in English. And from the accepted articles valuation, multicriteria methods and a quality tool were found both applicated in decision-making support. Also, all the criteria, sub-criteria and attributes applicated by all the 11 authors in the methods were presented in this article and they were classified in 12 factors to simplify them.

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Copyright of Dyna is the property of Universidad Nacional de Colombia, Medellin, Facultad de Minas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)