TY - JOUR
T1 - Current trends in artificial intelligence in reproductive endocrinology
AU - Bhaskar, Dhananjay
AU - Chang, T. Arthur
AU - Wang, Shunping
N1 - Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.
PY - 2022/8/1
Y1 - 2022/8/1
N2 - Purpose of reviewArtificial Intelligence, a tool that integrates computer science and machine learning to mimic human decision-making processes, is transforming the world and changing the way we live. Recently, the healthcare industry has gradually adopted artificial intelligence in many applications and obtained some degree of success. In this review, we summarize the current applications of artificial intelligence in Reproductive Endocrinology, in both laboratory and clinical settings.Recent findingsArtificial Intelligence has been used to select the embryos with high implantation potential, proper ploidy status, to predict later embryo development, and to increase pregnancy and live birth rates. Some studies also suggested that artificial intelligence can help improve infertility diagnosis and patient management. Recently, it has been demonstrated that artificial intelligence also plays a role in effective laboratory quality control and performance.SummaryIn this review, we discuss various applications of artificial intelligence in different areas of reproductive medicine. We summarize the current findings with their potentials and limitations, and also discuss the future direction for research and clinical applications.
AB - Purpose of reviewArtificial Intelligence, a tool that integrates computer science and machine learning to mimic human decision-making processes, is transforming the world and changing the way we live. Recently, the healthcare industry has gradually adopted artificial intelligence in many applications and obtained some degree of success. In this review, we summarize the current applications of artificial intelligence in Reproductive Endocrinology, in both laboratory and clinical settings.Recent findingsArtificial Intelligence has been used to select the embryos with high implantation potential, proper ploidy status, to predict later embryo development, and to increase pregnancy and live birth rates. Some studies also suggested that artificial intelligence can help improve infertility diagnosis and patient management. Recently, it has been demonstrated that artificial intelligence also plays a role in effective laboratory quality control and performance.SummaryIn this review, we discuss various applications of artificial intelligence in different areas of reproductive medicine. We summarize the current findings with their potentials and limitations, and also discuss the future direction for research and clinical applications.
KW - artificial intelligence
KW - embryo assessment
KW - infertility
KW - machine learning
KW - ploidy prediction
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U2 - 10.1097/GCO.0000000000000796
DO - 10.1097/GCO.0000000000000796
M3 - Review article
C2 - 35895955
AN - SCOPUS:85135373830
SN - 1040-872X
VL - 34
SP - 159
EP - 163
JO - Current Opinion in Obstetrics and Gynecology
JF - Current Opinion in Obstetrics and Gynecology
IS - 4
ER -