Intel and the U.S. National Aeronautics and Space Administration (NASA) Frontier Development Lab (FDL) jointly conducted the first radiation-based cancer research utilizing rodent and human data, and developed the first algorithm demonstrating biological markers that measure cancer progression stages.

Intel announced on the 19th that Intel AI Mentors and researchers from the NASA Frontier Development Lab (FDL) jointly conducted groundbreaking health research on astronauts to better understand the physiological effects of radiation exposure on space explorers.

The FDL developed the first algorithm demonstrating biological markers that measure cancer progression stages by combining radiation exposure data from laboratory mice and humans using Intel artificial intelligence (AI) technology.

Paul Duckworth, FDL researcher, stated, "With Intel's assistance, we formalized how causal machine learning models operate on data located in different places without physically moving the data. We achieved our goal of better understanding, improving, and supporting astronaut health using customized algorithms at the FDL 2021 forum," and added, "The results of this research are highly valuable and will eventually benefit not only astronauts participating in the International Space Station, future space stations, and the upcoming 2024 lunar exploration missions, but also cancer patients on Earth."

Space radiation can penetrate multiple layers of steel and aluminum and affect human biological tissue during space travel. This can cause health problems for astronauts and may lead to future cancer complications. With little data available on the effects of space radiation on astronauts from existing space exploration missions, researchers utilized human astronaut datasets that are strictly protected under various institutions. Intel and the FDL built causal machine learning that enables training AI algorithms on data stored in separate locations without data sharing across the entire federation of collaborating institutions to access these fragmented data.

Patrick Foley, Intel senior technology mentor, stated, "The FDL's astronaut health management team achieved remarkable results in two key objectives this year: newly combining human and mouse data and identifying multiple cancer-causing genes," and said, "This research demonstrates what public and private institutions can achieve when they collaborate, as well as how federated learning can be used for discoveries that might otherwise remain hidden. We are confident that this research will support astronaut health and enrich the lives of all people on Earth."