Ultrasound AI's study validates advanced AI for predicting delivery timing using standard ultrasound images.
Key Details
- 1Ultrasound AI, in collaboration with University of Kentucky, published results in The Journal of Maternal-Fetal & Neonatal Medicine.
- 2The AI predicts time to delivery using only standard ultrasound images, not relying on clinical history or other risk factors.
- 3In a large cohort (over 2 million images, thousands of patients), the AI achieved an R² of 0.95 for term and 0.92 for all births.
- 4Continuous retraining improved AI's prediction of preterm births, with R² increasing from 0.48 (V1) to 0.72 (V4).
- 5Technology is scalable, non-invasive, and functions well across all trimesters and diverse patient populations.
Why It Matters
Accurate prediction of delivery timing, especially preterm births, remains a persistent challenge. This AI-driven approach, requiring only routine ultrasound images, could significantly improve pregnancy management and outcomes worldwide, particularly in under-resourced settings.

Source
EurekAlert
Related News

•EurekAlert
MIT Introduces Interactive AI System for Fast Medical Image Annotation
MIT researchers have developed MultiverSeg, an interactive AI tool enabling efficient, user-driven segmentation of biomedical image datasets without prior model training.

•EurekAlert
Study Finds Gaps in FDA Safety Reporting for AI Medical Devices
A study highlights insufficient standardized safety and efficacy assessments for FDA-cleared AI/ML medical devices.

•EurekAlert
UCLA Unveils Light-Based AI System for Energy-Efficient Image Generation
Researchers at UCLA have developed an optical generative AI model that creates images using minimal energy and computational steps.