Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review. (15th September 2021)

• Record Type: Journal Article
• Authors: Chen, Zhiyi; Wang, Ziyao; Du, Meng; Liu, Zhenyu
• Is Part Of: Journal of ultrasound in medicine. Volume 41:Number 6(2022)
• Page Start: 1343
• Page End: 1353
• Publication Date: 2021-09-15
• Subjects: artificial intelligence -- endometrial receptivity -- infertility -- ovarian response -- ultrasound; Ultrasonics in medicine -- Periodicals; Ultrasonics; Ultrasonography; Ultrasonics in medicine; Electronic journals; Periodicals; Periodicals; 616.07543
• DOI: 10.1002/jum.15827
• Languages: English
• ISSNs: 0278-4297

Abstract

Abstract : The incidence of infertility is continuously increasing nearly all over the world in recent years, and novel methods for accurate assessment are of great need. Artificial Intelligence (AI) has gradually become an effective supplementary method for the assessment of female reproductive function. It has been used in clinical follicular monitoring, optimum timing for transplantation, and prediction of pregnancy outcome. Some literatures summarize the use of AI in this field, but few of them focus on the assessment of female reproductive function by AI‐aided ultrasound. In this review, we mainly discussed the applicability, feasibility, and value of clinical application of AI in ultrasound to monitor follicles, assess endometrial receptivity, and predict the pregnancy outcome of in vitro fertilization and embryo transfer (IVF‐ET). The limitations, challenges, and future trends of ultrasound combined with AI in providing efficient and individualized evaluation of female reproductive function had also been mentioned.