According to a study by a British startup, a new algorithm can determine male fertility faster and more accurately than before Bayezian.
The breakthrough comes amid growing problems for couples trying to conceive.
A recent report by the World Health Organization estimates that one in six people worldwide is now affected by infertility. Despite the belief that it’s a “woman thing,” men now contribute about 50% of fertility problems.
In fact, the male factor has become a growing problem. Recent studies have found that Sperm count has fallen by more than 50% in the last 45 years, with a rate of decline that has doubled since 2000. Up to 7% of men are now affected by infertility diagnosisIs can be slow, expensive and inconsistent.
These issues have prompted calls for better fertility testing. About 18 months ago, Bayezian was asked for help. The company, which provides data science and machine learning incubation services, applied AI to the problem.
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“We consider accurate diagnosis to be a crucial tool in improving male fertility.
Bayezian searched the MHSMA dataset for a solutiona collection of sperm images from 235 patients with male infertility. Each image is labeled by experts for normal or abnormal sperm acrosome, head, vacuole, and tail, which has made it an attractive data set for machine learning studies.
Use of the recordThe research group has developed deep learning frameworks that can detect the morphology of a sperm.
According to Bayezian, their algorithm detects differences that the human eye cannot perceive. The company says it’s possible Identify sperm fertility with 96% accuracy – 2% higher than existing scientific approaches.
“This project is the perfect example of the tech-for-good approach the team is taking,” said Ed Dixon, Founder and CEO of Bayezian. “We consider accurate diagnosis to be a crucial tool in improving male fertility.”