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Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstruction of airflow from the lungs. Symptoms include shortness of breath, coughing, production of mucus (sputum), and wheezing. It is typically caused by long-term exposure to irritating gases or particulate matter, most often cigarette smoke. People with chronic obstructive pulmonary disease are at increased risk of developing heart disease, lung cancer, and several other conditions (1).
Air travels down the trachea and reaches the lungs through two large tubes (bronchi). Inside the lungs, these tubes divide many times, like the branches of a tree, into smaller tubes (bronchioles) that terminate in clusters of small air sacs (alveoli) (1). Your lungs rely on the natural elasticity of the bronchi and air sacs to force air out of your body. COPD causes them to lose their elasticity and over-expand, leaving some air trapped in the lungs when exhaling. As the disease worsens, it is more difficult to carry out normal daily activities, often due to shortness of breath. The disease can have considerable financial consequences due to limited productivity at work and at home and the cost of medical treatment. COPD patients often have other conditions, such as heart disease, osteoporosis, musculoskeletal disorders, lung cancer, depression, or anxiety (3).
Using structured numeric, categorical, hybrid, and unstructured text data enables predictive models to capture COPD symptoms and discriminate against diseases with similar symptoms (2).
This solution uses feature importance in medications, health conditions, risk factors, and patient age as a a set of key EMR symptoms to discover COPD.
