2024
RADT-12. DERIVING IMAGING BIOMARKERS FOR PRIMARY CENTRAL NERVOUS SYSTEM LYMPHOMA USING DEEP LEARNING
Zhu J, Hager T, Chadha S, Sritharan D, Weiss D, Hossain S, Osenberg K, Moore N, Aneja S. RADT-12. DERIVING IMAGING BIOMARKERS FOR PRIMARY CENTRAL NERVOUS SYSTEM LYMPHOMA USING DEEP LEARNING. Neuro-Oncology 2024, 26: viii74-viii74. PMCID: PMC11553274, DOI: 10.1093/neuonc/noae165.0296.Peer-Reviewed Original ResearchPrimary central nervous system lymphomaWhole-brain radiotherapyTreated with chemotherapyOverall survivalHigh-risk groupPatient phenotypesCentral nervous system lymphomaPCNSL treatmentRisk of neurocognitive side effectsImaging biomarkersC-statisticOne-year OSTwo-year OSNervous system lymphomaAssociated with improved outcomesLog-rank testNeurocognitive side effectsTime-dependent AUCBrain radiotherapySystem lymphomaTumor volumeTumor sizeRisk stratificationAnalyses assessed differencesSub-analysis
2019
Applications of artificial intelligence in neuro-oncology.
Aneja S, Chang E, Omuro A. Applications of artificial intelligence in neuro-oncology. Current Opinion In Neurology 2019, 32: 850-856. PMID: 31609739, DOI: 10.1097/wco.0000000000000761.Peer-Reviewed Original ResearchConceptsArtificial intelligenceArtificial intelligence algorithmsNatural language processingAmount of dataIntelligence algorithmsLanguage processingIntelligenceNeuro-oncologyImage analysisApplicationsAlgorithmRisk stratificationFuture innovationsTreatment responseBrain tumorsClinical practiceClassificationRecent applicationsProcessingSignificant promiseChallengesDetection