The algorithm is able to predict how CRC will progress. Nicholas Chia, PhD, the co-director of the Mayo Clinic Center for Individualized Medicine’s microbiome program said, “We have information from this algorithm in terms of what event came first, what events are most important and exactly what the path to cancer was or what it will be.”
Rochester, Minn.-based Mayo and the NASA Frontier Development lab will work for eight weeks to optimize the algorithm for causal modeling.
John Kalantari, PhD, a machine learning scientist with Mayo, said: “We had a eureka moment when we realized that if we viewed our patient cancers as the result of an optimal game of cell evolution, then we could use inverse reinforcement learning techniques to learn the optimal ‘moves’ and environmental conditions that enable cancer progression, metastasis, recurrence, immune system evasion, and/or changes in treatment efficacy.”
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