Patricia Harte, Margaret M Barry
A scoping review of the implementation and cultural adaptation of school-based mental health promotion and prevention interventions in low-and middle-income countries
Global mental health (Cambridge, England)
air pollution events categorized extreme nonextreme basis magnitude severity highrisk extreme air pollution events exert disastrous effect environment therefore public health policymaking authorities must able determine characteristics events study proposes probabilistic machine learning technique predicting classification extreme nonextreme events basis data features address issue use nave bayes model prediction air pollution classes proposed leverage simplicity well high accuracy efficiency case study conducted air pollution index data klang malaysia period january 01 1997 august 31 2020 trained nave bayes model achieves high accuracy sensitivity specificity training test datasets therefore nave bayes model easily applied air pollution analysis providing promising solution accurate efficient prediction extreme nonextreme air pollution events findings study provide reliable information public authorities monitoring managing sustainable air quality time