Health IT Analytics September 16, 2020
The deep learning tool performed better than trained clinicians in selecting the highest-quality embryos for implementation.
A deep learning system was able to choose the most high-quality embryos for in-vitro fertilization (IVF) with 90 percent accuracy, according to a study published in eLife.
When compared with trained embryologists, the deep learning model performed with an accuracy of approximately 75 percent while the embryologists performed with an average accuracy of 67 percent.
The average success rate of IVF is 30 percent, researchers stated. The treatment is also expensive, costing patients over $10,000 for each IVF cycle with many patients requiring multiple cycles in order to achieve successful pregnancy.
While multiple factors determine the success of IVF cycles, the challenge of non-invasive...
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