OBJECTIVE: To evaluate combinations of candidate biomarkers to develop a multiplexed prediction model for identifying the viability and location of an early pregnancy. In this study, we assessed 24 biomarkers with multiple machine learning-based meth...
OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive techniques (ART).
Endometriosis affects 1 in 9 women and those assigned female at birth. However, it takes 6.4 years to diagnose using the conventional standard of laparoscopy. Noninvasive imaging enables a timelier diagnosis, reducing diagnostic delay as well as the ...
OBJECTIVE: To report an uncommon case of primary OP treated laparoscopically. Ectopic pregnancy (EP) is the leading cause of maternal mortality during the first trimester and the incidence increases with assisted reproductive techniques, occurring in...
OBJECTIVE: To describe a novel high-precision technique for robotic excision of uterine isthmocele, employing a carbon dioxide laser fiber, under hysteroscopic guidance, and near-infrared guidance.
OBJECTIVE: To develop a machine learning model designed to predict the time of ovulation and optimal fertilization window for performing intrauterine insemination or timed intercourse (TI) in natural cycles.