AI Medical Compendium Topic

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Embryology

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Consistency and objectivity of automated embryo assessments using deep neural networks.

Fertility and sterility
OBJECTIVE: To evaluate the consistency and objectivity of deep neural networks in embryo scoring and making disposition decisions for biopsy and cryopreservation in comparison to grading by highly trained embryologists.

Artificial intelligence in human in vitro fertilization and embryology.

Fertility and sterility
Embryo evaluation and selection embody the aggregate manifestation of the entire in vitro fertilization (IVF) process. It aims to choose the "best" embryos from the larger cohort of fertilized oocytes, the majority of which will be determined to be n...

Artificial intelligence-the future is now.

Journal of assisted reproduction and genetics
The pros and cons of artificial intelligence in assisted reproductive technology are presented.

Comparing the performance of artificial intelligence learning models to medical students in solving histology and embryology multiple choice questions.

Annals of anatomy = Anatomischer Anzeiger : official organ of the Anatomische Gesellschaft
INTRODUCTION: The appearance of artificial intelligence language models (AI LMs) in the form of chatbots has gained a lot of popularity worldwide, potentially interfering with different aspects of education, including medical education as well. The p...

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...

Machine learning approaches for image classification in developmental biology and clinical embryology.

Development (Cambridge, England)
The rapid increase in the amount of available biological data together with increasing computational power and innovative new machine learning algorithms has resulted in great potential for machine learning approaches to revolutionise image analysis ...