Health Imaging June 21, 2022
Hannah Murphy

Researchers recently developed and validated a deep learning model that can identify trisomy 21 in the first trimester of a pregnancy based on findings from ultrasound images. 

Trisomy 21—a chromosomal anamoly that causes developmental delays and intellectual disabilities—can be detected via ultrasound and cell-free fetal DNA validation. While DNA screening is up to 99% accurate, it comes at the cost of a high price tag and some studies have suggested that other more cost-effective options, such as ultrasound, should be explored.  

When using ultrasound, providers measure fetal nuchal translucency (NT) thickness and other measurements as a reliable way to confirm and rule out Trisomy 21. The accuracy of these measurements depends greatly on the sonographer completing the exam though, which is a cause for concern...

Today's Sponsors

H1
ZeOmega
Holon

Today's Sponsors

Institute for Healthcare Improvement
Crossover Health

Today's Sponsor

Institute for Healthcare Improvement

 
Topics: AI (Artificial Intelligence), Provider, Radiology, Technology
Artificial Intelligence Improves Endoscopy Detection Rates, Reporting
Unlocking the power of AI-driven pathology in drug development: An Interview with Bristol Myers Squibb
Why distributed AI is key to pushing the AI innovation envelope
Biologists train AI to generate medicines and vaccines
AI-driven device could surpass limits of traditional vital signs for predicting patient deterioration