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During assisted reproductive technology treatment, embryo selection is an important process that may affect the clinical pregnancy rate. Many assisted reproductive technology units over the world have tried different approaches to increase the clinical pregnancy rate. Conventionally, the morphology of the embryo is assessed by the embryologist with naked eyes only. Nowadays, artificial intelligence (AI) has been used to assist in morphological assessment of the embryo. Our pilot study showed that the AI-enhanced morphokinetic (MK) analysis increased the accuracy in embryo selection by \~9%, while the detection rate for abnormal chromosomes in embryo has also been increased by Raman spectroscopy (RS) analysis. The combined MK-RS analysis will be able to complete embryo assessment within 5-6 days after fertilization. This method needs shorter time and is at lower cost when compared to inva
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