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
2023
Comparing Detection Schemes for Adversarial Images against Deep Learning Models for Cancer Imaging
Joel M, Avesta A, Yang D, Zhou J, Omuro A, Herbst R, Krumholz H, Aneja S. Comparing Detection Schemes for Adversarial Images against Deep Learning Models for Cancer Imaging. Cancers 2023, 15: 1548. PMID: 36900339, PMCID: PMC10000732, DOI: 10.3390/cancers15051548.Peer-Reviewed Original ResearchAdversarial imagesDeep learning modelsDL modelsDetection modelLearning modelConvolutional neural networkDetection schemeAdversarial detectionDefense techniquesMachine learningMedical imagesAdversarial perturbationsInput imageAdversarial trainingNeural networkArt performanceMagnetic resonance imagingGradient descentPixel valuesHigh accuracyImagesBrain magnetic resonance imagingAbsence of malignancyClassificationScheme
2022
Machine Learning Applications for Differentiation of Glioma from Brain Metastasis—A Systematic Review
Jekel L, Brim WR, von Reppert M, Staib L, Petersen G, Merkaj S, Subramanian H, Zeevi T, Payabvash S, Bousabarah K, Lin M, Cui J, Brackett A, Mahajan A, Omuro A, Johnson MH, Chiang VL, Malhotra A, Scheffler B, Aboian MS. Machine Learning Applications for Differentiation of Glioma from Brain Metastasis—A Systematic Review. Cancers 2022, 14: 1369. PMID: 35326526, PMCID: PMC8946855, DOI: 10.3390/cancers14061369.Peer-Reviewed Original ResearchBrain metastasesDifferentiation of gliomasMagnetic resonance imagingEligible studiesSystematic reviewSingle-center institutionConventional magnetic resonance imagingSpecific clinical circumstancesNon-invasive differentiationQuality of reportingClinical circumstancesPoor reportingClinical practiceModel assessmentResonance imagingMetastasisStudy designGliomasTRIPOD StatementMultiple studiesExternal validationClinical translationAdherenceDifferentiationReview