ReviewZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2025
[Progress in the application of artificial intelligence in assisted reproduction].
Review in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
6 authors.
Funding
Abstract
As a disease that seriously affects the health of men and women of childbearing age, the incidence of infertility is increasing worldwide, and the popularization of assisted reproductive technology (ART) is expected to improve the situation. However, invitro fertilization and embryo transfer (IVF) success rates are only about 50%, and IVF success rates are affected by a number of factors. For example, semen quality, endometrial thickness, fallopian tube patency, embryo selection and transplantation, uterine microenvironment, etc., and the treatment process of IVF is highly dependent on the clinical experience of embryologists, and there is a lack of objective and unified evaluation criteria. Artificial intelligence (AI) is ideally suited to processing and analyzing large, dynamic temporal data sets to assist physicians in making more objective and precise decisions, thereby improving IVF success. At present, artificial intelligence technology using different types of algorithms has been used for sperm classification, oocyte and embryo selection, and prediction of embryo development after implantation, etc. The application of AI in the field of assisted reproduction is expected to improve infertility diagnosis results and increase the pregnancy rate and live birth rate of ART, but there are still certain controversies in privacy, safety and other aspects.In the future, with the accumulation of high-quality datasets, algorithm optimization and the advancement of imaging technology, AI is expected to increase the success rate of ART by selecting higher-quality sperm and oocytes, as well as embryos with greater developmental potential. This will bring significant innovation to the field of reproductive medicine and the entire healthcare sector, while also reducing treatment costs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.