Preterm Birth Prediction

Sano Team: Szymon Płotka, Arkadiusz Sitek

Goal: Preterm Birth Prediction based on fetal transvaginal ultrasound videos using Deep Learning methods

Collaboration:

• University Centre of Mother and Child’s Health, Medical University of Warsaw
• Michał Lipa, Medical University of Warsaw
• Tomasz Trzciński, Warsaw University of Technology

Data:

• 200 independent fetal transvaginal US recordings

Preliminary results:

• Deep learning methods are promising for preterm birth prediction
• Physical biomarkers could be a good preterm birth indicator
• Publication in preparation