Automated machine learning predicts male infertility based on Johnsen score
Infertility affects females and males equally. In male infertility, azoospermia (a medical condition with no sperm in semen) is a major problem that prevents a couple from having a child.
For the treatment of patients with azoospermia, testicular sperm extraction (TESE) is required to obtain mature sperms. When examined, histological specimens are typically given a score, called the Johnsen score, on a scale of 1 to 10, based on the histopathological features of the testis.
The Johnsen score has been widely used in urology since it was first reported 50 years ago. However, histopathological evaluation of the testis is not an easy task and takes much time due to the complexity of testicular tissue arising from the multiple, highly specialized steps in spermatogenesis.
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IMAGE: All images are X400 magnification. Algorithm performance using Google Cloud AutoML Vision, Average precision recall curve for image dataset, magnification X400. view more
Credit: Hideyuki Kobayashi
Infertility affects females and males equally. In male infertility, azoospermia (a medical condition with no sperm in semen) is a major problem that prevents a couple from having a child. For the treatment of patients with azoospermia, testicular sperm extraction (TESE) is required to obtain mature sperms. When examined, histological specimens are typically given a score, called the Johnsen score, on a scale of 1 to 10, based on the histopathological features of the testis.