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Reproductive Techniques, Assisted

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An artificial neural network for the prediction of assisted reproduction outcome.

Journal of assisted reproduction and genetics
PURPOSE: To construct and validate an efficient artificial neural network (ANN) based on parameters with statistical correlation to live birth, to be used as a comprehensive tool for the prediction of the clinical outcome for patients undergoing ART.

Empathetic application of machine learning may address appropriate utilization of ART.

Reproductive biomedicine online
The value of artificial intelligence to benefit infertile patients is a subject of debate. This paper presents the experience of one aspect of artificial intelligence, machine learning, coupled with patient empathy to improve utilization of assisted ...

Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data.

Journal of assisted reproduction and genetics
Over the past years, the assisted reproductive technologies (ARTs) have been accompanied by constant innovations. For instance, intracytoplasmic sperm injection (ICSI), time-lapse monitoring of the embryonic morphokinetics, and PGS are innovative tec...

Mining of variables from embryo morphokinetics, blastocyst's morphology and patient parameters: an approach to predict the live birth in the assisted reproduction service.

JBRA assisted reproduction
Based on growing demand for assisted reproduction technology, improved predictive models are required to optimize in vitro fertilization/intracytoplasmatic sperm injection strategies, prioritizing single embryo transfer. There are still several obsta...

Data sharing: using blockchain and decentralized data technologies to unlock the potential of artificial intelligence: What can assisted reproduction learn from other areas of medicine?

Fertility and sterility
The extension of blockchain use for nonfinancial domains has revealed opportunities to the health care sector that answer the need for efficient and effective data and information exchanges in a secure and transparent manner. Blockchain is relatively...

Using Deep Learning in a Monocentric Study to Characterize Maternal Immune Environment for Predicting Pregnancy Outcomes in the Recurrent Reproductive Failure Patients.

Frontiers in immunology
Recurrent reproductive failure (RRF), such as recurrent pregnancy loss and repeated implantation failure, is characterized by complex etiologies and particularly associated with diverse maternal factors. It is currently believed that RRF is closely a...

A machine learning system with reinforcement capacity for predicting the fate of an ART embryo.

Systems biology in reproductive medicine
The aim of this work was o construct a score issued from a machine learning system with self-improvement capacity able to predict the fate of an ART embryo incubated in a time lapse monitoring (TLM) system. A retrospective study was performed. For th...

Three ways of knowing: the integration of clinical expertise, evidence-based medicine, and artificial intelligence in assisted reproductive technologies.

Journal of assisted reproduction and genetics
Decision-making in fertility care is on the cusp of a significant frameshift. Online tools to integrate artificial intelligence into the decision-making process across all aspects of ART are rapidly emerging. These tools have the potential to improve...