Researchers at Osaka Metropolitan University have developed an AI-based method to categorize heart function and accurately identify valvular heart disease using chest X-rays, a breakthrough that could enhance patient outcomes. This aspect of AI application comes amidst challenges in diagnosing valvular heart disease, a major cause of heart failure, as it requires specialized skills for echocardiography that are in short supply. However, chest radiography is a common, accessible, and reproducible test to identify diseases and can also capture heart images.
To tackle these issues, Dr. Daiju Ueda’s team developed a model using AI to accurately classify cardiac functions and diagnose valvular heart diseases from chest radiographs. A total of 22,551 chest radiographs, paired with echocardiograms from 16,946 patients across four facilities, were used to train the AI model. The system successfully accurately classified six selected types of valvular heart disease. Dr. Ueda believes this research will improve doctors’ diagnostic efficiency and could be helpful in areas with no specialists, emergencies, and patients who cannot undergo echocardiography.
To tackle these issues, Dr. Daiju Ueda’s team developed a model using AI to accurately classify cardiac functions and diagnose valvular heart diseases from chest radiographs. A total of 22,551 chest radiographs, paired with echocardiograms from 16,946 patients across four facilities, were used to train the AI model. The system successfully accurately classified six selected types of valvular heart disease. Dr. Ueda believes this research will improve doctors’ diagnostic efficiency and could be helpful in areas with no specialists, emergencies, and patients who cannot undergo echocardiography.
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