A model based on PDCA and data mining approach for the prevention of occupational accidents in the plumbing activity in the construction sector.

Background: Occupational accidents in the plumbing activity in the construction sector in developing countries have high rates of work absenteeism. The productivity of enterprises is heavily influenced by it.

Objective: To propose a model based on the Plan, Do, Check, and Act cycle and data mining for the prevention of occupational accidents in the plumbing activity in the construction sector.

Multivariate analysis in data science for the geospatial distribution of the breast cancer mortality rate in Colombia.

This research is framed in the area of biomathematics and contributes to the epidemiological surveillance entities in Colombia to clarify how breast cancer mortality rate (BCM) is spatially distributed in relation to the forest area index (FA) and circulating vehicle index (CV). In this regard, the World Health Organization has highlighted the scarce generation of knowledge that relates mortality from tumor diseases to environmental factors. Quantitative methods based on geospatial data science are used with cross-sectional information from the 2018 census; it's found that the BCM in Colombia is not spatially randomly distributed, but follows cluster aggregation patterns.