• P Sandhya

Over the past two decades, Artificial Intelligence (AI) has emerged as a transformative tool across various domains, particularly in medical applications. Its adoption has significantly enhanced the effectiveness and efficiency of diagnosing and treating patients. Chronic Obstructive Pulmonary Disease (COPD), a progressive and obstructive lung disease encompassing emphysema and chronic bronchitis, has become the fourth leading cause of death globally due to its rising incidence and associated complications. This paper highlights the necessity for a Clinical Decision Support System (CDSS) tailored for COPD to assist physicians in delivering improved diagnostic and treatment strategies. We present the design and architecture of a CDSS for COPD, integrating advanced Machine Learning (ML) techniques such as Classifier Ensemble methods, Support Vector Machines, Neural Networks, Decision Trees, Random Forest, Logistic Regression, and Gradient Boosting. The proposed CDSS framework operates in three phases: data input (patient information, medical history, and spirometry results), ML-based analysis (staging and classification of COPD, prediction of comorbidities, and drug-drug interaction checks), and outcome generation (treatment recommendations, psychological assessment, smoking cessation modules, and disease management strategies). By leveraging AI and ML, the system enhances clinical decision-making, supports comprehensive patient management, and addresses both physical and psychological aspects of COPD, ultimately aiming to improve patient outcomes and healthcare delivery.

COPD, Ensemble Methods, Support Vector Machine, Neural Networks, Decision Trees, Treatment Strategies, Drug-Drug Interaction, Smoking Cessation, Disease Management, Healthcare Technology.

"Machine Learning-Based Clinical Decision Support System for the Diagnosis and Management of Chronic Obstructive Pulmonary Disease Using Embedded Feature Selection Methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.3, Issue 6, page no.427-432, June-2016, Available :http://www.jetir.org/papers/JETIR1701D15.pdf

"Machine Learning-Based Clinical Decision Support System for the Diagnosis and Management of Chronic Obstructive Pulmonary Disease Using Embedded Feature Selection Methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.3, Issue 6, page no. pp427-432, June-2016, Available at : http://www.jetir.org/papers/JETIR1701D15.pdf