This study plans to conduct clinical validation of the model in real clinical settings, comparing it with primary care physicians and specialist physicians to ensure the model's practicality. Through continuous optimization and practice, the study aims to use AI-assisted heart sound auscultation to empower the auscultation capabilities of primary care obstetricians, pediatricians, and non-cardiovascular specialists nationwide. This will not only reduce the missed diagnosis rate and improve the detection rate of existing CHD screenings, but also expand the coverage of current CHD screening networks, incorporating newborns, infants, preschool children, children, and adolescents aged 0-18 years into the screening scope. The study aims to establish a new benchmark in child health management by providing feasible and cost-effective child health management solutions for other developing countries, contributing to global efforts for the health of children.
See this in plain English?
AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Sensitivity of auscultation in identifying CHD between independent auscultation by primary care physicians and AI-assisted auscultation by primary care physicians
Timeframe: From enrollment to the end of treatment at 6 months