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Privacy Threats Against Federated Matrix Factorization
Matrix Factorization has been very successful in practical recommendatio...
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Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention
prevention of stroke with its associated risk factors has been one of th...
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Federated Transfer Learning for EEG Signal Classification
The success of deep learning (DL) methods in the Brain-Computer Interfac...
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Volumetric Attention for 3D Medical Image Segmentation and Detection
A volumetric attention(VA) module for 3D medical image segmentation and ...
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Validating uncertainty in medical image translation
Medical images are increasingly used as input to deep neural networks to...
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Finding novelty with uncertainty
Medical images are often used to detect and characterize pathology and d...
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Validation and Optimization of Multi-Organ Segmentation on Clinical Imaging Archives
Segmentation of abdominal computed tomography(CT) provides spatial conte...
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Outlier Guided Optimization of Abdominal Segmentation
Abdominal multi-organ segmentation of computed tomography (CT) images ha...
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Stochastic tissue window normalization of deep learning on computed tomography
Tissue window filtering has been widely used in deep learning for comput...
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Contrast Phase Classification with a Generative Adversarial Network
Dynamic contrast enhanced computed tomography (CT) is an imaging techniq...
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Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision
Human in-the-loop quality assurance (QA) is typically performed after me...
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HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography
Electroencephalography (EEG) classification techniques have been widely ...
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Towards Universal Object Detection by Domain Attention
Despite increasing efforts on universal representations for visual recog...
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