Application of machine learning algorithms in building health diagnostics: predictive analytics evaluating indoor air quality and sick building syndrome in educational settings
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Ismail, Syazwan Aizat Ismail
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Abstract
Description
This dataset contains epidemiological and exposure assessment data used to develop and validate a predictive analytics model for diagnosing sick building syndrome (SBS) in learners. It includes responses from a modified MM040NA SBS questionnaire alongside simultaneous indoor air quality (IAQ) physical parameters, demonstrating the application of neural networks in classifying IAQ health risks.
Keywords
Epidemiology , Public Health , Data Mining , Machine Learning , Environmental Impacts , Environmental Health