In Life sciences in space research
The advent of artificial intelligence (AI) has a promising role in the future long-duration spaceflight missions. Traditional AI algorithms rely on training and testing data from the same domain. However, astronaut medical data is naturally limited to a small sample size and often difficult to collect, leading to extremely limited datasets. This significantly limits the ability of traditional machine learning methodologies. Transfer learning is a potential solution to overcome this dataset size limitation and can help improve training time and performance of a neural networks. We discuss the unique challenges of space medicine in producing datasets and transfer learning as an emerging technique to address these issues.
Waisberg Ethan, Ong Joshua, Kamran Sharif Amit, Paladugu Phani, Zaman Nasif, Lee Andrew G, Tavakkoli Alireza
2023-Feb
Machine learning, Small datasets, Space medicine, Transfer learning
