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
Study Warns: AI Alone Is Not Enough in Critical Healthcare Decisions
Evaluating both AI algorithms and human users is key for safe adoption in high-stakes healthcare settings, according to an Ohio State study.
•EurekAlert
AI-Assisted Colonoscopies May Reduce Clinicians’ Detection Skills, Study Finds
Routine use of AI in colonoscopies linked to decreased skill in adenoma detection by clinicians without AI assistance.
•EurekAlert
AI Voice Analysis Shows Promise for Early Laryngeal Cancer Detection
Researchers demonstrated AI could detect early laryngeal cancer from voice recordings, distinguishing it from benign conditions.