Clinical applications of digital twin technology in In Vitro Fertilisation.
David B Olawade, Oluwadamilola Racheal Abe, Elizabeth Kelechi Nwazuo et al.
✦ AI-curated · Sources linked
In 30 seconds
This narrative review explores the applications of digital twin technology in in vitro fertilisation (IVF), highlighting its potential to enhance embryo selection, ovarian response prediction, and treatment personalization. The review synthesizes evidence from various studies, indicating that digital twin technology could significantly improve IVF outcomes, although large-scale randomized controlled trials are still needed.
Key findings
- Digital twin technology shows promise in embryo development simulation and ovarian response prediction.
- Early evidence indicates improved accuracy in embryo selection and treatment protocol optimization.
- Integration of AI and machine learning enhances the creation of comprehensive virtual models in IVF.
Why it matters
Digital twin technology could revolutionize IVF by enabling more personalized and predictive treatment strategies, potentially leading to higher success rates and better patient outcomes. Understanding its applications is crucial for advancing reproductive medicine.