While used in pond snail embryos for this study, in future the technique could be used to help accelerate understanding on how climate change, and other external factors, affect humans and animals in the earliest stages of life.
The use of video means features ranging from the first heartbeat, or crawling behaviour, through to shell formation or hatching are reliably detected by Dev-ResNet, and has revealed sensitivities of different features to temperature not previously known. The work was led by PhD candidate, Ziad Ibbini, who studied BSc Conservation Biology at the University, before taking a year out to upskill himself in software development, then beginning his PhD. He designed, trained and tested Dev-ResNet himself.
"The only real limitations are in creating the data to train the deep learning model -- we know it works, you just need to give it the right training data. "This milestone would not have been possible without deep learning, and it is exciting to think of where this new capability will lead us in the study of animals during their most dynamic period of life."The early stages of embryonic development contain many of life's mysteries. Unlocking these mysteries can help us better understand early development and birth defects, and help develop new ...