Machine Learning Could Boost the Success Rate of In Vitro Fertilization (IVF)
takyon writes:
Artificial intelligence in healthcare is often a story of percentages. One 2017 study predicted AI could broadly improve patient outcomes [open, DOI: 10.7717/peerj.7702] [DX] by 30 to 40 percent. Which makes a manifold improvement in results particularly noteworthy.
In this case, according to one Israeli machine learning startup, AI has the potential to boost the success rate of in vitro fertilization (IVF) by as much as 3x compared to traditional methods. In other words, at least according to these results, couples struggling to conceive that use the right AI system could be multiple times more likely to get pregnant.
The Centers for Disease Control and Prevention defines assisted reproductive technology (ART) as the process of removing eggs from a woman's ovaries, fertilizing it with sperm and then implanting it back in the body.
The overall success rate of traditional ART is less than 30%, according to a recent study [open, DOI: 10.5455/aim.2019.27.205-211] [DX] in the journal Acta Informatica Medica.
But, says Daniella Gilboa, CEO of Tel Aviv, Israel-based AiVF-which provides an automated framework for fertility and IVF treatment-help may be on the way. (However, she also cautions against simply multiplying 3x with the 30% traditional ART success rate quoted above. "Since pregnancy is very much dependent on age and other factors, simple multiplication is not the way to compare the two methods," Gilboa says.)
Journal Reference:
Abhimanyu S. Ahuja. The impact of artificial intelligence in medicine on the future role of the physician, PeerJ (DOI: 10.7717/peerj.7702)
Read more of this story at SoylentNews.