@article {28137,
	title = {Artificial intelligence in the fertility clinic: status, pitfalls and possibilities},
	journal = {Human Reproduction},
	volume = {36},
	year = {2021},
	month = {07/2021},
	pages = {2429 - 2442},
	publisher = {Oxford Academic},
	abstract = {In recent years, the amount of data produced in the field of ART has increased exponentially. The diversity of data is large, ranging from videos to tabular data. At the same time, artificial intelligence (AI) is progressively used in medical practice and may become a promising tool to improve success rates with ART. AI models may compensate for the lack of objectivity in several critical procedures in fertility clinics, especially embryo and sperm assessments. Various models have been developed, and even though several of them show promising performance, there are still many challenges to overcome. In this review, we present recent research on AI in the context of ART. We discuss the strengths and weaknesses of the presented methods, especially regarding clinical relevance. We also address the pitfalls hampering successful use of AI in the clinic and discuss future possibilities and important aspects to make AI truly useful for ART.},
	issn = {0268-1161},
	doi = {10.1093/humrep/deab168},
	url = {https://academic.oup.com/humrep/article/36/9/2429/6330662},
	author = {Riegler, Michael and M H {Stensen} and Witczak, O and J M {Andersen} and Hicks, Steven and Hugo Lewi {Hammer} and Delbarre, E and Halvorsen, P{\r a}l and Yazidi, A and Holst, N and T B {Haugen}}
}
