A Clinical Decision Support System for COPD was designed incorporating machine learning techniques such as Classifier Ensemble methods, Support Vector Machine, Neural Networks, and Decision Trees.
The paper proposes a Clinical Decision Support System using machine learning techniques to assist physicians in diagnosing and treating COPD.
In last two decades, Artificial Intelligence (AI) has become a major tool in every domain in general and medical applications in particular. AI is globally accepted and used for designing medical applications to support medical practitioners in diagnosing and treating patients effectively and efficiently. Chronic Obstructive Pulmonary Disease (COPD) is a kind of obstructive lung disease. Patients suffering from COPD makes breathing uneasy. COPD's incidence of sickness and death rates are rising and it is now the fourth leading cause of death globally. In this paper, we are discussing need for Clinical Decision Support System (CDSS) for COPD which helps the physicians to provide better and effective diagnosis and treatment strategies. In addition, we have designed a CDSS for COPD which is discussed in detail in this paper. The CDSS encompasses Machine Learning techniques like Classifier Ensemble methods, Support Vector Machine, Neural Networks, and Decision Trees.
Anakal et al. (Fri,) conducted a other in Chronic Obstructive Pulmonary Disease (COPD). Clinical Decision Support System (CDSS) using Machine Learning was evaluated. A Clinical Decision Support System for COPD was designed incorporating machine learning techniques such as Classifier Ensemble methods, Support Vector Machine, Neural Networks, and Decision Trees.
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