A new model based on artificial intelligence to screening preterm birth.

Objective: The objective of this study is to create a new screening for spontaneous preterm birth (sPTB) based on artificial intelligence (AI).

Methods: This study included 524 singleton pregnancies from 18th to 24th-week gestation after transvaginal ultrasound cervical length (CL) analyzes for screening sPTB < 35 weeks. AI model was created based on the stacking-based ensemble learning method (SBELM) by the neural network, gathering CL < 25 mm, multivariate unadjusted logistic regression (LR), and the best AI algorithm.

Cervical pessary plus vaginal progesterone in a singleton pregnancy with a short cervix: an experience-based analysis of cervical pessary's efficacy.

Background: Several studies were published about cervical pessary, with controversial results. These studies demonstrated that the patient follow-up after pessary insertion is very different between the study centers and the number of pessary insertions per center was often <30 cases. This study aims to determine cervical pessary performance in singleton pregnancies with a short cervix based on a single center learning curve.