Application of artificial neural networks in reproductive medicine

Abstract

With the emergence of the age of information, the data on reproductive medicine has improved immensely. Nonetheless, healthcare workers who wish to utilise the relevance and implied value of the various data available to aid clinical decision-making encounter the difficulty of statistically analysing such large data. The application of artificial intelligence becoming widespread in recent years has emerged as a turning point in this regard. Artificial neural networks (ANNs) exhibit beneficial characteristics of comprehensive analysis and autonomous learning, owing to which these are being applied to disease diagnosis, embryo quality assessment, and prediction of pregnancy outcomes. The present report aims to summarise the application of ANNs in the field of reproduction and analyse its further application potential.

Keywords:

• Artificial intelligence
• artificial neural networks
• assisted reproduction
• embryo quality assessment
• personalised diagnosis and treatment
• prediction model

Acknowledgements

Yuan completed literature generalizing and drafted the manuscript. Lv was responsible for proofreading and typeseting. Hao revised the details and finalized the manuscript. All authors read and approved the final manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by the [National Nature Fund] under [Grant number 81671416].