Advances in artificial intelligence in the non-invasive diagnosis of molecular markers of glioma
Early diagnosis of molecular markers of glioma is crucial for its treatment and prognosis,and high-throughput imaging features extracted from MR images of glioma based on artificial intelligence algorithms have become potential noninvasive biomarkers for predicting the molecular pathological subtype of glioma,opening the era of"molec-ular imaging"of glioma.This study aims to review the literature on the application of artificial intelligence algorithms in lesion segmentation in MR images of glioma and the construction of non-invasive diagnostic molecular markers such as radiomics or imaging genomics,in order to determine that artificial intelligence can make non-invasive predictions of glioma molecular biomarkers and provide a reliable basis for assisting clinicians in making decisions.
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