Using deep-learning in fetal ultrasound analysis for diagnosis of cystic hygroma in the first trimester.

Objective: To develop and internally validate a deep-learning algorithm from fetal ultrasound images for the diagnosis of cystic hygromas in the first trimester.

Methods: All first trimester ultrasound scans with a diagnosis of a cystic hygroma between 11 and 14 weeks gestation at our tertiary care centre in Ontario, Canada were studied. Ultrasound scans with normal nuchal translucency were used as controls.

The impact of nurses' and physicians' shift change on obstetrical outcomes.

Purpose: To evaluate the effect around nurses' shift change and on-call physicians' shift change on obstetrical outcomes.

Methods: A retrospective study of women who had an attempt of labor in a single-medical center, January 2006-December 2017. Obstetrical outcomes were compared between the time around nurses' shift change (6:00-8:00, 14:00-16:00, and 22:00-00:00) to the rest of the day, and between the time around on-call physicians' shift change (6:00-8:00, 14:00-16:00) to the rest of the day.