Current applications of artificial intelligence in assisted reproductive technologies

Area of Science:

• Reproductive endocrinology and infertility
• Medical artificial intelligence

Background:

• Artificial intelligence (AI) is transforming healthcare through advanced data analysis and predictive modeling.
• Machine learning algorithms analyze diverse data for optimizing reproductive endocrinology and infertility treatments.

Purpose of the Study:

• To review the latest evidence on AI design, implementation, and validation in assisted reproductive technologies (ART).
• To categorize AI applications in embryology and clinical workflows within ART.
• To highlight ethical considerations associated with AI tools in fertility treatments.

Main Methods:

• Comprehensive literature search of PubMed and MEDLINE databases.
• Inclusion of publications from 2020 onwards, plus select seminal earlier works.
• Categorization of findings based on AI application areas and ethical concerns.

Main Results:

• AI tools are actively used in fertility clinics and embryology labs for gamete selection and quality improvement.
• Evidence demonstrates AI's role in enhancing diagnostics and optimizing treatment plans.
• Ethical concerns, data bias, and regulatory issues are identified challenges.

Conclusions:

• AI integration in reproductive medicine shows potential for improved success rates and accessibility.
• Continued evolution of AI is expected to further enhance infertility treatments.
• Addressing challenges is crucial for realizing the full potential of AI in fertility care.