Alife Research and Publications
We are committed to publishing our research as we work towards improving outcomes and fertility care for all
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Scientific Abstract
Selection of optimal gonadotropin dose using machine learning may be associated with improved outcomes and reduced utilization of FSH
October 24th, 2022
ASRM
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Ovarian Stimulation
Maximizing number of oocytes retrieved increases number of 2PNs, blastocysts, and cumulative live birth rates, without impairing primary transfer live birth rates
October 24th, 2022
ASRM
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Ovarian Stimulation
A new approach to estimating cumulative live birth rates using predicted outcomes of all embryos
October 24th, 2022
ASRM
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IVF Outcomes
A novel approach for retrospectively estimating the efficiency of PGT-A testing
October 24th, 2022
ASRM
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PGT-A Testing
A comprehensive model for predicting the probability of live birth prior to the start of progesterone during artificial FET cycles
October 24th, 2022
ASRM
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IVF Outcomes
Ovarian stimulation outcomes improve on successive retrieval cycles regardless of change in gonadotropin dose or protocol
October 24th, 2022
ASRM
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Ovarian Stimulation
An interpretable machine learning model for individualized gonadotropin starting dose selection during ovarian stimulation
July 28th, 2022
Ovarian Stimulation
Sensitivity analysis of an embryo grading artificial intelligence model to different focal planes
June 30th, 2022
ESHRE
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Embryo Grading
An expected benefit analysis of using an interpretable machine learning model for optimizing the day of trigger during ovarian stimulation
June 30th, 2022
ESHRE
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Ovarian Stimulation
Large-scale simulation of pregnancy rate improvements using an AI model for embryo ranking
June 30th, 2022
ESHRE
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Embryo Grading
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Designed For
Diversity, Equity, & Inclusion
As part of our vision to see a world where AI-powered fertility care is accessible for all families, we have committed to building a dataset that is demographically representative of the U.S. population. Today, our 2.4 million rows of data make up the largest and most diverse IVF dataset in the field, ensuring that our AI models will serve anybody hoping to build a family.
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