Hari Ilangovan

Jun 10, 2024 | nature.com | Katherine A. Hoadley |Hari Ilangovan |Robin Elgart

AbstractNASA has employed high-throughput molecular assays to identify sub-cellular changes impacting human physiology during spaceflight. Machine learning (ML) methods hold the promise to improve our ability to identify important signals within highly dimensional molecular data. However, the inherent limitation of study subject numbers within a spaceflight mission minimizes the utility of ML approaches.