P –104 Assessment of sperm motility according to WHO classification using convolutional neural networks

AbstractStudy questionHow does convolutional neural network (CNN)-predicted sperm motility correlate with manual assessment according to the WHO guidelines.Summary answerCNN predicts sperm motility comparable to reference laboratories in the ESHRE-SIGA External Quality Assessment Programme for Semen Analysis.What is known alreadyManual sperm motility assessment according to WHO guidelines is regarded as the gold standard. To obtain reliable and reproducible results, comprehensive training is essential as well as running internal and external quality control. Prediction based on artificial intelligence can potentially transfer human-level performance into models that perform the task faster and can avoid human assessor variations. CNNs have been groundbreaking in image processing. To develop AI models with high predictive power, the data set used should be of high quality and sperm motility assessment based on WHO guidelines.Study design, size, durationVideos of 65 fresh semen samples obtained from the ESHRE-SIGA External Quality Assessment Programme for Semen Analysis (from the period 2006 –2018) were used in the development of the model. One video was captured for each semen sample. Sperm motility data was obtained from manual assessment of the videos according to WHO criteria by reference laboratories in the programme. Rapid progressive motility was also included. Ten-fold cross-v alidation was used to compensate for the relatively small dataset.Participants/materials, se...
Source: Human Reproduction - Category: Reproduction Medicine Source Type: research