Data mining applied to cancer work-related
DOI:
https://doi.org/10.59681/2175-4411.v16.2024.1014Keywords:
Data Mining, Occupational Cancer, Chemical ProductsAbstract
Objective: To find association rules between the worker's occupation, the chemical exposed and the cancer diagnosed in 2019. Method: Data Mining techniques were applied, within the Knowledge Discovery in Databases process. To identify patterns and correlations, files on Work-Related Cancer – available from the Notification Aggravities Information System –, the Weka software and the Apriori algorithm were used. Results: We present 2 rules with the "Confidence" metric and 4 rules with the "Conviction" metric, which indicated strong associations between "Multipurpose agricultural producer", "Solar radiation", "Other malignant skin neoplasms and related diseases'' and "Non-ionizing radiation and Pesticide". Conclusion: The results may encourage organizations to develop prevention strategies against occupational cancer, in order to maintain and ensure the quality of life and safety of workers, especially workers belonging to occupations with higher risk of cancer exposure.
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