AI Enables Non-Invasive, Accurate Screening for Down Syndrome in the First Trimester

Now researchers from the Institute of Automation of the Chinese Academy of Sciences (CASIA) have developed an intelligent prediction model to achieve non-invasive screening of Down Syndrome using ultrasound image. This work was published in JAMA Network Open on June 21. For decades, ultrasound images have been widely used for screening fetuses with Down Syndrome due to the method's safety, convenience, and low cost. However, using common ultrasound indicators, detection accuracy is less than 80% in actual ultrasound examinations. Invasive methods such as villus biopsy, amniocentesis, and fetal umbilical venipuncture are also commonly used to detect Down Syndrome.