A groundbreaking study led by the University of Plymouth unveils a new deep learning AI model capable of tracking embryonic development in real-time using video footage. Published in the *Journal of Experimental Biology*, the research introduces “Dev-ResNet,” which accurately identifies crucial developmental events in pond snails, such as heart function, crawling, hatching, and even mortality.
#### 3D Model Revolutionizes Developmental Analysis Unlike traditional methods reliant on still images, this study pioneers a 3D model that harnesses changes observed between video frames. Dev-ResNet leverages these dynamic features to discern developmental milestones, offering unprecedented insights into the sensitivity of various traits to environmental factors like temperature.
#### Versatile Application Across Species While demonstrated on pond snail embryos, Dev-ResNet’s versatility extends across species boundaries. The authors provide accessible scripts and documentation for implementing this innovative tool in diverse biological systems, promising broad applicability and transformative impact on developmental biology research.
#### Potential for Climate Change Research The AI’s ability to monitor developmental responses to external stimuli positions it as a powerful tool for investigating how climate change and other environmental stressors affect both humans and animals. By accelerating our understanding of developmental dynamics, Dev-ResNet opens new avenues for proactive conservation efforts.
#### Visionary Leadership and Future Prospects The project, spearheaded by Ph.D. candidate Ziad Ibbini and supervised by Dr. Oli Tills, underscores the University of Plymouth’s longstanding commitment to advancing developmental physiology research. Driven by deep learning capabilities, this milestone marks a paradigm shift in our comprehension of organismal development, paving the way for transformative discoveries in this field.
