Covering Fertility: Humanity to AI
In this podcast, we share how Univfy use AI/ML to help more people use fertility care to have a family. We also discuss barriers limiting fertility care and IVF access, factors impacting affordability of care and ways to think about IVF cost and success. We will break down the technical side of AI/ML, research and medicine in fertility care into digestible concepts.
Covering Fertility: Humanity to AI
Using AI - machine learning to support IVF patient counseling and the impact on IVF usage
This podcast discusses the research publication by Yao et al, Journal of Clinical Medicine 2024, titled "Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective Multicenter Experience".
Briefly, Univfy and their collaborators examined the impact of patient-centric artificial intelligence and machine learning (AI/ML) tools on the utilization of In Vitro Fertilization (IVF) services.
Check out:
- Dr. Mylene Yao's related LinkedIn post: https://bit.ly/4jkll2N
- The actual research article: https://bit.ly/3Z2c6gl
Created with Google Notebook LM. Content reviewed and approved by Univfy.
This podcast discusses the research performed by Univfy and their collaborators to examine the impact of patient-centric artificial intelligence and machine learning (AI/ML) tools on the utilization of In Vitro Fertilization (IVF) services. Researchers conducted a retrospective study reviewing over 24,000 new fertility patients across 7 fertility centers at over 30 locations in US and Canada to determine if using an AI-powered prognostic report, specifically the Univfy report, was associated with a higher rate of patients starting IVF treatment.
The findings suggest that exposure to the Univfy report was indeed linked to an increased likelihood of patients converting to IVF compared to those who did not receive the report. The study also explores factors influencing treatment decisions within the group using the report, noting that older age was a small but independent predictor of IVF initiation after accounting for individual center characteristics.