AI applied to IVF
We have teamed up with some of the brightest minds in AI and Reproductive health to develop an AI Co-Pilot specialising in IVF
FOCUSED AI
Through personal experiences through several IVF cycles and discussions with healthcare professionals we noticed that generalist AI is being used in the healthcare field. An AI that summarizes books and writes business plans is definitely not the best choice when it comes to health. FOCUStron decided it is time for a FOCUSED AI, it's all in our name.
IVF
Augmented AI with a specialised repository and expert input from the leading IVF surgeons will lead to a quantum leap in progress. This is the future of reproductive health and an issue critical to the future of mankind. With plunging birthrates around the world we would argue this is even more important than getting to Mars.
IVF-Llama
AI Driven Clinical Support for Personalised Fertility Care
Infertility is a significant global health issue, with the World Health Organization (WHO) estimating that 1.3 billion people worldwide are affected. In Singapore, as in many countries, the success rates of Assisted Reproductive Technologies (ART) such as in-vitro fertilization (IVF) remain low, particularly as women age, with only 6.4% success for women over 40. The socio-economic burden is immense: the high costs of IVF cycles, long time-to-pregnancy, and the need for multiple cycles make treatment inaccessible to many, especially those from lower-income groups. Furthermore, the variability in clinical decision-making, regulatory barriers, and ethical concerns exacerbate social disparities, limiting access to optimal treatment. These challenges hinder equitable access to fertility treatments, with poorer success rates affecting those who cannot afford multiple cycles or access specialized care.
How IVF-Llama Tackles the Issue:
IVF-Llama addresses these socio-economic challenges by providing an AI-driven clinical decision support tool for IVF treatments. This solution offers personalized, data-driven recommendations, reducing reliance on subjective clinical judgment, which often leads to variability in outcomes. By incorporating multiple predictors for success—such as maternal health, sperm quality, and other critical factors—IVF-Llama enhances the precision and effectiveness of treatment planning.
This improved decision-making process has a profound impact on the socio-economic issue at hand. IVF-Llama can potentially shorten the time-to-pregnancy by optimizing treatment protocols, thereby reducing the number of costly IVF cycles needed. By making IVF more efficient and personalized, it can lower overall treatment costs, increase success rates, and make ART more accessible to a broader population, particularly those who are economically disadvantaged. This also helps tackle healthcare inequities by ensuring that treatment plans are guideline-compliant and standardized, reducing variability based on socio-economic status.
