Danish Study Evaluates AI Preterm Birth Prediction Across Different Cervical Ultrasound Settings — Clinical Practice Implications
247 Health News Editorial
·28 May 2026
·3 min read
·clinical-trialsDanish researchers are evaluating how different ultrasound imaging settings affect AI model performance in predicting preterm birth. This 2,000-patient study addresses critical questions about implementing AI diagnostic tools in routine obstetric practice.
Originally reported by ClinicalTrials.gov
References
- 1.Rigshospitalet. (2024). The Impact of Image Acquisition in Cervical Ultrasound on AI-Based Prediction of Preterm Birth in Clinical Practice: A Prospective Observational Study. ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07598097
- 2.Iams, J. D., Goldenberg, R. L., Meis, P. J., Mercer, B. M., Moawad, A., Das, A., ... & Caritis, S. N. (1996). The length of the cervix and the risk of spontaneous premature delivery. New England Journal of Medicine, 334(9), 567-572. https://doi.org/10.1056/NEJM199602293340904
- 3.Rajkomar, A., Dean, J., & Kohane, I. (2019). Machine learning in medicine. New England Journal of Medicine, 380(14), 1347-1358. https://doi.org/10.1056/NEJMra1814259
- 4.Berghella, V., Palacio, M., Ness, A., Alfirevic, Z., Nicolaides, K. H., & Saccone, G. (2009). Cervical length screening for prevention of preterm birth in singleton pregnancy with threatened preterm labor. American Journal of Obstetrics and Gynecology, 200(5), 486-e1. https://doi.org/10.1016/j.ajog.2009.06.015
- 5.Society for Maternal-Fetal Medicine. (2021). SMFM Special Statement: Implementation of artificial intelligence (AI) in obstetrics and gynecology. American Journal of Obstetrics and Gynecology, 225(4), 387-392. https://doi.org/10.1016/j.ajog.2021.04.265
- 6.Chawanpaiboon, S., Vogel, J. P., Moller, A. B., Lumbiganon, P., Petzold, M., Hogan, D., ... & Gülmezoglu, A. M. (2019). Global, regional, and national estimates of levels of preterm birth in 2014. The Lancet Global Health, 7(1), e37-e46. https://doi.org/10.1016/S2214-109X(18)30451-0
- 7.Honest, H., Bachmann, L. M., Gupta, J. K., Kleijnen, J., & Khan, K. S. (2002). Accuracy of cervical transvaginal sonography in predicting preterm birth. Ultrasound in Obstetrics and Gynecology, 19(3), 305-311. https://doi.org/10.1046/j.1469-0705.2002.00811.x
- 8.Koivu, A., Sairanen, M., Airola, A., Laitinen, L., Savolainen, J., Halmesmäki, E., ... & Grönroos, T. (2022). Predicting risk of stillbirth and preterm pregnancies with machine learning. Scientific Reports, 12(1), 5354. https://doi.org/10.1038/s41598-022-10710-z
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247 Health News Editorial
247 Health News is a medical intelligence platform delivering evidence-based research appraisals, clinical trial monitoring, and health technology news for healthcare professionals.
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