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Basics of Artificial Intelligence for Assisted Reproductive Technologies
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Author(s): Aylin Gökhan (Faculty of Medicine, Ege University, Turkey), Kubilay Dogan Kilic (Faculty of Medicine, Ege University, Turkey), Türker Çavuşoğlu (Faculty of Medicine, Izmir Bakırçay University, Turkey)and Yiğit Uyanıkgil (Faculty of Medicine, Ege University, Turkey)
Copyright: 2024
Pages: 12
Source title:
Enhancing Medical Imaging with Emerging Technologies
Source Author(s)/Editor(s): Avinash Kumar Sharma (Sharda University, India), Nitin Chanderwal (University of Cincinnati, USA), Shobhit Tyagi (Sharda University, India), Prashant Upadhyay (Sharda University, India)and Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/979-8-3693-5261-8.ch001
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Abstract
In the field of assisted reproductive technologies (ART), each cycle brings high cost and long-term clinical and laboratory studies. In order to eliminate the negative effects of this process on families, the necessity of standardized ART protocols that can be applied to each individual with low cost and fast results is essential. Although artificial intelligence has the potential to respond strongly to this need, the integration of artificial intelligence into ART is slower compared to other branches of medicine. Increasing understanding of artificial intelligence by researchers will accelerate this integration. In order to understand and be able to use artificial intelligence, this chapter will first discuss the conceptual confusion in artificial neural networks, deep learning, machine learning, and artificial intelligence. Finally, gaps will be filled with artificial intelligence-related application areas and examples in ART.
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