Glioma Detection
Description
High-risk molecular markers play a key role in glioma grading, survival, and prognosis, but current genetic testing methods are invasive and time-consuming. Advanced magnetic resonance imaging (MRI) offers a non-invasive alternative that may reflect pathological features associated with these markers, although it struggles with glioma heterogeneity. This study explores Artificial intelligence (AI) imaging, which has emerged as an efficient non-invasive method for identifying high-risk molecular markers in gliomas, with ongoing research addressing its potential and challenges.
Creator
Shanxi Medical University
Information
Pediatrics or Adult
Adult
Speciality
Neurology
Modality
MRI
Training
Github
Publication
FDA