This program is designed to provide decision-makers, policymakers and professional working in policy with a foundational understanding of AI technology.
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Background: Understanding the relationship between the Omics and the phenotype is a central problem in precision medicine. The high dimensio… (see more)nality of metabolomics data challenges learning algorithms in terms of scalability and generalization. Most learning algorithms do not produce interpretable models -- Method: We propose an ensemble learning algorithm based on conjunctions or disjunctions of decision rules. -- Results : Applications on metabolomics data shows that it produces models that achieves high predictive performances. The interpretability of the models makes them useful for biomarker discovery and patterns discovery in high dimensional data.