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
AI Framework Adapts Smartphone Audio for Pediatric Lung Sound Screening
Researchers developed a domain-adaptive deep learning model enabling smartphones to detect abnormal lung sounds in children for remote screening.
•EurekAlert
AI Tool Predicts Stroke Risk by Analyzing Genomic Data, Eyes Imaging Next
Researchers developed a transformer-based AI model to predict ischaemic stroke risk using genetic data, with plans to integrate imaging.
•EurekAlert
HKU Launches Centre for Health AI Research and Translation
The University of Hong Kong has established the Centre for Health AI Research and Translation (CHART) to drive trustworthy, patient-centered AI innovation in healthcare.