AIMC Topic: Fertilization in Vitro

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An interpretable artificial intelligence approach to differentiate between blastocysts with similar or same morphological grades.

Human reproduction (Oxford, England)
STUDY QUESTION: Can a quantitative method be developed to differentiate between blastocysts with similar or same inner cell mass (ICM) and trophectoderm (TE) grades, while also reflecting their potential for live birth?

Artificial intelligence-driven analysis of embryo morphokinetics in singleton, twin, and triplet pregnancies.

Human reproduction (Oxford, England)
In recent years, the transfer of more than one embryo has become less frequent to diminish multiple pregnancies. Even so, there is still a risk of one embryo splitting into two or even three. This report presents the case of a triamniotic monochorion...

The 'golden fleece of embryology' eludes us once again: a recent RCT using artificial intelligence reveals again that blastocyst morphology remains the standard to beat.

Human reproduction (Oxford, England)
Grading of blastocyst morphology is used routinely for embryo selection with good outcomes. A lot of effort has been placed in IVF to search for the prize of selecting the most viable embryo to transfer ('the golden fleece of embryology'). To improve...

Time will tell: time-lapse technology and artificial intelligence to set time cut-offs indicating embryo incompetence.

Human reproduction (Oxford, England)
STUDY QUESTION: Can more reliable time cut-offs of embryo developmental incompetence be generated by combining time-lapse technology (TLT), artificial intelligence, and preimplantation genetics screening for aneuploidy (PGT-A)?

Leveraging artificial intelligence for advancements in reproductive health.

African journal of reproductive health
We are writing to address the growing interest in the role of artificial intelligence (AI) within healthcare, particularly in the field of reproductive health. As technology continues to evolve, AI offers an unprecedented opportunity to transform how...

[Application of the blastomere count variations "skip value" in the embryo AI assessment].

Zhonghua fu chan ke za zhi
To explore the correlation between blastomere count variations "skip value" which extracted from by time-lapse technology (TLT) combined with artificial intelligence (AI) and morphological features of in vitro fertilization (IVF) embryo, and to test...

Embryonic Quality Assessment using Advanced Deep Learning Architectures utilizing Microscopic Images of Blastocysts.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The accurate evaluation of embryonic quality which is a key aspect in Assisted Reproductive Technology (ART) and it is crucial to ensure the success of in vitro fertilization (IVF), especially at critical developmental phases like day 3 and day 5. To...

Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images.

Human reproduction (Oxford, England)
STUDY QUESTION: Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts?

BlastAssist: a deep learning pipeline to measure interpretable features of human embryos.

Human reproduction (Oxford, England)
STUDY QUESTION: Can the BlastAssist deep learning pipeline perform comparably to or outperform human experts and embryologists at measuring interpretable, clinically relevant features of human embryos in IVF?

Deep Learning-Based Quantitative Blastocyst Assessment.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Selecting the single best blastocyst based on morphological appearance for implantation is a crucial part of in vitro fertilization (IVF). Various deep learning and computer vision-based methods have recently been applied for assessing blastocyst qua...