Abstract
Chronic Obstructive Pulmonary Disease (COPD) is an irreversible airway obstruction with a high societal burden. Although smoking is known to be the biggest risk factor, additional components need to be considered. In this study, we aim to identify COPD risk factors by applying machine learning models that integrate sociodemographic, clinical, and genetic data to predict COPD development.Clinical relevance- This study assessed the risk factors of COPD in sociodemographic, clinical, and genetic data. We have determined that sociodemographic factors are highly associate to the development of COPD.
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