AIMC Topic: Fertilization in Vitro

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Opportunities for artificial intelligence in healthcare and in vitro fertilization.

Fertility and sterility
Artificial intelligence (AI) is understandably garnering an increased share of voice in the general and specialized media. The recent release of several generative AI products has added "touchable" context to fears of the potential negative effects o...

An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization.

Scientific data
Medical Assisted Reproduction proved its efficacy to treat the vast majority forms of infertility. One of the key procedures in this treatment is the selection and transfer of the embryo with the highest developmental potential. To assess this potent...

Development and validation of deep learning based embryo selection across multiple days of transfer.

Scientific reports
This work describes the development and validation of a fully automated deep learning model, iDAScore v2.0, for the evaluation of human embryos incubated for 2, 3, and 5 or more days. We trained and evaluated the model on an extensive and diverse dat...

New frontiers in embryo selection.

Journal of assisted reproduction and genetics
Human infertility is a major global public health issue estimated to affect one out of six couples, while the number of assisted reproduction cycles grows impressively year over year. Efforts to alleviate infertility using advanced technology are gai...

Advancements in the future of automating micromanipulation techniques in the IVF laboratory using deep convolutional neural networks.

Journal of assisted reproduction and genetics
PURPOSE: To determine if deep learning artificial intelligence algorithms can be used to accurately identify key morphologic landmarks on oocytes and cleavage stage embryo images for micromanipulation procedures such as intracytoplasmic sperm injecti...

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...

Sperm-cell DNA fragmentation prediction using label-free quantitative phase imaging and deep learning.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
In intracytoplasmic sperm injection (ICSI), a single sperm cell is selected and injected into an egg. The quality of the chosen sperm and specifically its DNA fragmentation have a significant effect on the fertilization success rate. However, there i...

Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization.

Sensors (Basel, Switzerland)
Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. In vitro fertilization (IVF) is one of those assisted reproduction methods in which the sperm and egg...

Automation in ART: Paving the Way for the Future of Infertility Treatment.

Reproductive sciences (Thousand Oaks, Calif.)
In vitro fertilisation (IVF) is estimated to account for the birth of more than nine million babies worldwide, perhaps making it one of the most intriguing as well as commoditised and industrialised modern medical interventions. Nevertheless, most IV...

An artificial intelligence model correlated with morphological and genetic features of blastocyst quality improves ranking of viable embryos.

Reproductive biomedicine online
RESEARCH QUESTION: Can better methods be developed to evaluate the performance and characteristics of an artificial intelligence model for evaluating the likelihood of clinical pregnancy based on analysis of day-5 blastocyst-stage embryos, such that ...