The goal of this Views and Interviews series was to bring together the thought leaders in the field and envision what the laboratory will look like in the future. This consensus piece strives to take the thoughts of those leaders and develop themes a...
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...
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...
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...
Artificial intelligence (AI) has experienced rapid growth over the past few years, moving from the experimental to the implementation phase in various fields, including medicine. Advances in learning algorithms and theories, the availability of large...