Artificial intelligence (AI) systems have been proposed for reproductive medicine since 1997. Although AI is the main driver of emergent technologies in reproduction, such as robotics, Big Data, and internet of things, it will continue to be the engi...
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...
Predictive modeling has become a distinct subdiscipline of reproductive medicine, and researchers and clinicians are just learning the skills and expertise to evaluate artificial intelligence (AI) studies. Diagnostic tests and model predictions are s...
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...
Traditionally, new treatments have been developed for the population at large. Recently, large-scale genomic sequencing analyses have revealed tremendous genetic diversity between individuals. In diseases driven by genetic events such as cancer, geno...
As the world becomes increasingly reliant on computers, it is not surprising that medicine has embraced the computer age with enthusiasm. This is also true in the field of reproductive medicine, where we are witnessing exciting applications of digita...
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.