2024
Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI
Lost J, Ashraf N, Jekel L, von Reppert M, Tillmanns N, Willms K, Merkaj S, Petersen G, Avesta A, Ramakrishnan D, Omuro A, Nabavizadeh A, Bakas S, Bousabarah K, De Lin M, Aneja S, Sabel M, Aboian M. Enhancing Clinical Decision-Making: An Externally Validated Machine Learning Model for Predicting IDH Mutation in Gliomas using Radiomics from Pre-Surgical MRI. Neuro-Oncology Advances 2024, vdae157. DOI: 10.1093/noajnl/vdae157.Peer-Reviewed Original ResearchIsocitrate dehydrogenase mutation statusArea under the curveMagnetic resonance imagingMutation statusML modelsMachine learningSemi-automated tumour segmentationsPre-surgical magnetic resonance imagingCare of glioma patientsMachine learning modelsClinical care of glioma patientsIsocitrate dehydrogenase statusAnnotated datasetsFeature extractionPrediction taskMulti-institutional dataModel trainingIDH mutationsPredicting IDH mutationLearning modelsRetrospective studyHeterogeneous datasetsTumor segmentationGlioma patientsBrain tumors
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