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

Source
EurekAlert
Related News

Deep Learning AI Outperforms Clinic Prognostics for Colorectal Cancer Recurrence
A new deep learning model using histopathology images identifies recurrence risk in stage II colorectal cancer more effectively than standard clinical predictors.

AI Reveals Key Health System Levers for Cancer Outcomes Globally
AI-based analysis identifies the most impactful policy and resource factors for improving cancer survival across 185 countries.

Dual-Branch Graph Attention Network Predicts ECT Success in Teen Depression
Researchers developed a dual-branch graph attention network that uses structural and functional MRI data to accurately predict individual responses to electroconvulsive therapy in adolescents with major depressive disorder.