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This article discusses the use of supervised machine learning, specifically artificial neural networks, in the medical field for automating tasks and making predictions. The study focuses on identifying and training genetic and clinical features to identify patients with IDH-mutant glioma. The article also mentions the use of publicly available datasets and follows the STROBE reporting guideline.
