Understanding causal relationships is essential for biomedical applications. We leverage an ensemble of causal inference machine learning methods (CRISP) to identify genes whose expression is potentially causal of increased fat content in liver from spaceflown mice. Currently, we are working with a Crowdsourcing Contenders award to develop a version of CRISP that can identify causal features in both tabular and bio-imagery data.
Collaboration with Robots Go Mental – Guided Transfer Learning […]
Artificial Intelligence for Life in Space (AI4LS) – NASA
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