Journal of Clinical Respiratory Diseases & Care: Acesso Aberto

Machine Learning Approaches for Risk Stratification and Predictive Modeling of Asthma

Abstract

Pooja MR and Pushpalatha MP

Chronic respiratory diseases like Asthma and Chronic Obstructive Pulmonary Diseases (COPD) have attracted research interest in the area of risk stratification and many machine learning techniques have been the subject of interest in prediction systems involving risk stratification that perform  early identification of the risk factors for the disease. Identification of patient populations at high risk is an important intervention in the early detection and clinical assessment of chronic diseases like asthma, as it can lead to targeted and personalized therapies. Here, we propose and deploy different machine learning approaches for the risk stratification under different study settings. All the approaches primarily predict the disease outcome or identify the severity/control level by recognizing the key risk factors for the disease depending on the nature of the data made available.