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Table 1 Clinical application of AI in neuro-oncology

From: Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging

I—Gliomas
I—Differentiation of neoplastic from non-neoplastic lesions
 High-grade gliomas versus tumefactive demyelinating diseases
 Gliomas versus inflammation
II—Grading of gliomas
 Low versus high grade
 Grade II versus grade III
III—Radiogenomics
 Glioma
 Oligodendroglioma
IV—Pre-treatment evaluation
 Tumor segmentation
 Infiltration and extent
V—Prognostic value-survival
VI—Post-treatment evaluation
 Pseudo-progression
 Residual/recurrence versus post-treatment changes
II—Non glioma
Metastasis
PCNSL
Hemangioblastoma
III—Extra-axial brain tumors
Meningioma
Schwannoma
Pituitary adenoma
IV—Pediatric brain tumors
Characterization
Radiogenomics
  1. PCNSL primary central nervous system lymphoma