Artificial intelligence: empowering new insights into gamete and embryo development
<p indent="0mm">The development of sexual reproductive organism embryos begins with the fertilization process, where sperm and egg unite, followed by a series of intricate and orchestrated changes, leading to continuous embryo development and tissue differentiation, culminating in the formation of a complete biological individual. Conducting in-depth and systematic exploration of this intricate and complex process represents a monumental and challenging undertaking. Artificial intelligence, is aimed at emulating the human brain and assisting in addressing more complex problems. With the continuous updating of computing devices and the successive ascent of computing capabilities, artificial intelligence has experienced rapid development, achieving groundbreaking advancements in various fields. In the field of life sciences, artificial intelligence has a wide range of applications, especially in the study of gamete and embryo development, where it was applied in the relatively early days. From gamete selection to embryo quality assessment, and from investigating molecular mechanisms underlying embryo development to elucidating the interconnectedness among various modules during embryo development, including time, phenotype, and molecular features, artificial intelligence has been effectively utilized, demonstrating significant advantages. Hence, exploring how to better leverage artificial intelligence in the research process of gamete and embryo development is a question worthy of deeper investigation at this stage. This paper provides a comprehensive review of the current applications of artificial intelligence in gamete and embryo development research, along with an analysis of the challenges and directions for its future development.
Authors
- Zihuan Du
- Shuai Gao
Publication Details
- Journal
- Scientia Sinica Vitae
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1360/ssv-2024-0072
- Primary Topic
- Reproductive Biology and Fertility
- Type
- article
- Field-Weighted Citation Impact
- 0.00