Ensemble Learning Technique for Artificial Intelligence Assisted IVF Applications.

In-vitro fertilization (IVF) is considered one of the most effective assisted reproductive approaches. However, it involves a series of complex and expensive procedures, that result in approximately 30% success rate. New technological concepts, like deep learning (DL), are required to increase the success rate while simplifying the procedure. DL techniques can automatically extract valuable features from the available data, can be flexible, and can work efficiently on multiple problems. Motivated by these characteristics, in this work, a DL ensemble model is trained on a private dataset to classify blastocysts’ images. Further analysis is conducted to provide insights for future research.