EP02.24: Application of prenatal ultrasonic artificial intelligence quality control system in Shenzhen

Abstract

To improve the quality of prenatal ultrasound in Shenzhen, and reduce the incidence of birth defects, adopted the data of prenatal ultrasound images from 73 medical institutions and 1024 sonographers in Shenzhen, and evaluated the overall standard degree. Our AI quality control system applied to 2 years of ultrasonic images uploaded quarterly by 73 medical institutions in Shenzhen. Facing the data of different degree examinations, analyse the trend of the standard rate, basic standard rate, qualified rate, non-standard rate and missing section rate. Through intelligent quality control system, the trend of five indicators show that the quality control work is effective. Intelligent quality control balancing the development differences and has the characteristics of objectivity, efficiency and economy. It can realise large-scale ultrasonic images for all staff in a short time and help doctors to improve their understanding. So it is of profound significance especially for the improvement of doctors with low seniority and medical institutions with insufficient training resources. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Ähnliche Arbeiten