Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review.

Journal: Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
PMID: 34524706

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.

Authors

  • Zhiyi Chen
    School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, UCAS, Hangzhou, Zhejiang Province, China.
  • Ziyao Wang
    Department of Ophthalmology, Peking University Third Hospital, Beijing, China.
  • Meng Du
    Key Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China.
  • Zhenyu Liu
    School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.

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