Chronic　obstructive　pulmonary　disease　(COPD)　is　a　serious　chronic　respiratory　disease.　Improving　the　ability　to　identify　patients　with　COPD　in　primary　medical　institutions　is　important　to　prevent　and　treat　the　disease.　With　the　continuous　development　of　medical　digitization,　the　application　of　big　data　informatization　in　the　medical　and　health　fields　has　become　possible.　Recently,　applying　innovative　technologies　such　as　big　data　analysis,　machine　learning,　and　artificial　intelligence-Assisted　decision-making　in　the　medical　field　has　become　an　interdisciplinary　research　hotspot.　Based　on　the　identification　and　diagnosis　of　COPD　in　the　high-risk　population,　this　study　proposes　a　convenient　and　effective　clinical　decision　support　system　to　help　identify　patients　with　COPD　in　primary　health　institutions.　The　results　of　the　preliminary　experiments　show　that　the　proposed　method　is　convenient　and　effective　compared　with　the　existing　methods.　　©　1996-2012　Tsinghua　University　Press.