2025
Improving the Robustness of Deep-Learning Models in Predicting Hematoma Expansion from Admission Head CT.
Tran A, Karam G, Zeevi D, Qureshi A, Malhotra A, Majidi S, Murthy S, Park S, Kontos D, Falcone G, Sheth K, Payabvash S. Improving the Robustness of Deep-Learning Models in Predicting Hematoma Expansion from Admission Head CT. American Journal Of Neuroradiology 2025, ajnr.a8650. PMID: 39794133, DOI: 10.3174/ajnr.a8650.Peer-Reviewed Original ResearchFast Gradient Sign MethodDeep learning modelsRobustness of deep learning modelsAdversarial attacksAdversarial imagesAdversarial trainingSign MethodModel robustnessDeploying deep learning modelsDeep learning model performanceConvolutional neural networkImprove model robustnessAcute intracerebral hemorrhageHematoma expansionMulti-threshold segmentationReceiver operating characteristicIntracerebral hemorrhageGradient descentType attacksData perturbationNeural networkProjected GradientTraining setAntihypertensive Treatment of Acute Cerebral HemorrhageThreshold-based segmentation
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
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply