AI Medical Compendium Journal:
Fertility and sterility

Showing 21 to 30 of 51 articles

Three-dimensional imaging reconstruction and laparoscopic robotic surgery: a winning combination for a complex case of multiple myomectomy.

Fertility and sterility
OBJECTIVE: To demonstrate the intraoperative use of three-dimensional (3D) imaging reconstruction for a complex case of multiple myomectomy assigned to robot-assisted laparoscopic surgery.

Making and selecting the best embryo in the laboratory.

Fertility and sterility
Over the past 4 decades our ability to maintain a viable human embryo in vitro has improved dramatically, leading to higher implantation rates. This has led to a notable shift to single blastocyst transfer and the ensuing elimination of high order mu...

Automated rare sperm identification from low-magnification microscopy images of dissociated microsurgical testicular sperm extraction samples using deep learning.

Fertility and sterility
OBJECTIVE: To develop a machine learning algorithm to detect rare human sperm in semen and microsurgical testicular sperm extraction (microTESE) samples using bright-field (BF) microscopy for nonobstructive azoospermia patients.

Machine learning for prediction of euploidy in human embryos: in search of the best-performing model and predictive features.

Fertility and sterility
OBJECTIVE: To assess the best-performing machine learning (ML) model and features to predict euploidy in human embryos.

Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryos.

Fertility and sterility
OBJECTIVE: To perform a series of analyses characterizing an artificial intelligence (AI) model for ranking blastocyst-stage embryos. The primary objective was to evaluate the benefit of the model for predicting clinical pregnancy, whereas the second...

A machine learning algorithm can optimize the day of trigger to improve in vitro fertilization outcomes.

Fertility and sterility
OBJECTIVE: To determine whether a machine learning causal inference model can optimize trigger injection timing to maximize the yield of fertilized oocytes (2PNs) and total usable blastocysts for a given cohort of stimulated follicles.