Using Deep Learning as a means to improve male fertility outcomes.

Assisted reproductive technologies such as IVF are faced with the challenges of low success rates and high cost. Traditional methods of sperm cell analysis and selection for IVF are costly, time-consuming, and require skillful clinicians who employ non-standardised procedures.

The aim of the microfluidics project is to bring deep learning to the challenge of improving male fertility outcomes, by applying state-of-the-art machine learning technologies to sperm cell analysis and selection. This opens up exciting possibilities to create effective, and highly accurate tools with real-world applications for researchers and clinicians.