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Rare diseases (RDs) are complicated health conditions that are difficult to be managed at several levels. The scarcity of available data chiefly determines an intricate scenario even for experts and specialized clinicians, which in turn leads to the so called "diagnostic odyssey" for the patient. This situation calls for innovative solutions to support the decision process via quantitative and automated tools. Machine learning brings to the stage a wealth of powerful inference methods; however,doi:10.3389/fmed.2021.747612 pmid:34676229 pmcid:PMC8523988 fatcat:yvmg3n4m2fcb5k43lvhen2r4o4