HIGHLIGHTS
SUMMARY
Han adopted a novel evolutionary algorithm, the conjunctive clause evolutionary algorithm (CCEA), to select major features to better characterize individuals with ASD, thus demonstrating how machine_learning tools might implement diagnostic models in ASD. All these approaches underline the increasing role of machine_learning‐based diagnostic classification in improving clinical decisions. The authors propose here a machine_learning based approach, which uses genetic data retrieved from VariCarta to evaluate their possible impact on specific ASD endophenotypic characteristics. The technique of using embeddings as a vectorial space to identify similarities be‐ tween elements has been borrowed from the . . .
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