research/
18 pages · Updated July 19, 2026
Pages
- A higher number of oocytes retrieved is associated with an increase in 2PNs, blastocysts, and cumulative live birth rates
- Causal inference indicates that poor responders have similar outcomes with the antagonist protocol compared with flare
- An artificial intelligence model to predict upcoming embryology workload for patients undergoing ovarian stimulation
- Evaluation of the effect on ongoing pregnancy rate of using artificial intelligence for embryo prioritization: An interim analysis of a prospective randomized control trial
- Post-market analysis of an AI-powered clinical decision support tool for ovarian stimulation
- Clinical Evaluation of an Image-Based Artificial Intelligence Model for Embryo Selection: A Double-Blinded Randomized Comparative Reader Study
- Using a Machine Learning Model for Identifying an Individualized Optimal Starting FSH Dose
- Optimizing oocyte Yield Utilizing a Machine Learning Model for Dose and Trigger Decisions: A Multi-center, Prospective Study
- Optimizing Oocyte Yield Utilizing a Machine Learning Model for Dose and Trigger Decisions, A Multi-Center, Prospective Study.
- A blastocyst’s implantation potential is linked to its originating oocyte cohort’s blastulation rate: evidence for a cohort effect
- An artificial intelligence model to predict upcoming patient oocyte collections to help optimize efficiency and safety in the embryology laboratory.
- Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryos
- Clinical evaluation of an image-based artificial intelligence model for embryo selection: a double-blinded randomized comparative reader study
- IVF Research and Publications | Alife
- Clinical evaluation of a machine learning model for embryo selection: A double-blinded randomized comparative reader study
- Evaluation of Artificial Intelligence for Embryo Selection During IVF: A Prospective, Randomized Controlled Trial
- An interpretable machine learning model for individualized gonadotropin starting dose selection during ovarian stimulation
- An interpretable machine learning model for predicting the optimal day of trigger during ovarian stimulation