.png){kind=logo}
Use AI to identify COPD in patients using key EMR symptoms.
Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstruction of airflow from the lungs (1). 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. COPD patients are at increased risk of developing heart disease, lung cancer, and several other conditions (1). Approximately 10% of Canadians aged 35 and over are living with COPD (2). Globally, COPD is the third leading cause of death, causing 3.23 million deaths in 2019 (3). Nearly 90% of COPD deaths in children under 70 occur in low- and middle-income countries (3). COPD causes the bronchi and air sacs in the lungs to lose their elasticity and over-expand, trapping air in the lungs during exhalation (1). This leads to difficulty in carrying out normal daily activities due to shortness of breath and has significant financial consequences due to reduced productivity and medical treatment costs (3). COPD patients often suffer from other conditions, including heart disease, osteoporosis, musculoskeletal disorders, lung cancer, depression, and anxiety (3).
To improve diagnostic precision, an predictive model, "COPDDetect AI," has been crafted utilizing varied data inputs from electronic medical records to accurately discern COPD symptoms and distinguish the condition from other respiratory ailments, leveraging information on patient health conditions, medication history, and exposure risks.
The model is enhanced by a synthetic data set, built on the basis of careful analysis of real-world data. Social determinants of health (SDoH) provide contextual information about environmental and social factors that may influence health outcomes. These data are complemented by the clinical experience on COPD symptomatology from the Mayo Clinic (1), the findings on the predictive role of AI in COPD by Zafari et al. (2), and the WHO's comprehensive overview of the prevalence and global impact of COPD (3), ensuring that the model is aligned with current medical knowledge and practices.
Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstruction of airflow from the lungs (1). 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. COPD patients are at increased risk of developing heart disease, lung cancer, and several other conditions (1). Approximately 10% of Canadians aged 35 and over are living with COPD (2). Globally, COPD is the third leading cause of death, causing 3.23 million deaths in 2019 (3). Nearly 90% of COPD deaths in children under 70 occur in low- and middle-income countries (3). COPD causes the bronchi and air sacs in the lungs to lose their elasticity and over-expand, trapping air in the lungs during exhalation (1). This leads to difficulty in carrying out normal daily activities due to shortness of breath and has significant financial consequences due to reduced productivity and medical treatment costs (3). COPD patients often suffer from other conditions, including heart disease, osteoporosis, musculoskeletal disorders, lung cancer, depression, and anxiety (3).
To improve diagnostic precision, an predictive model, "COPDDetect AI," has been crafted utilizing varied data inputs from electronic medical records to accurately discern COPD symptoms and distinguish the condition from other respiratory ailments, leveraging information on patient health conditions, medication history, and exposure risks.
The model is enhanced by a synthetic data set, built on the basis of careful analysis of real-world data. Social determinants of health (SDoH) provide contextual information about environmental and social factors that may influence health outcomes. These data are complemented by the clinical experience on COPD symptomatology from the Mayo Clinic (1), the findings on the predictive role of AI in COPD by Zafari et al. (2), and the WHO's comprehensive overview of the prevalence and global impact of COPD (3), ensuring that the model is aligned with current medical knowledge and practices.
