Machine Learning Methods for Cancer Classification Using Gene Expression Data: A Review by Fadi Alharbi, Aleksandar Vakanski

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Soft-Label Supervised Meta-Model with Adversarial Samples for Uncertainty Quantification by Kyle Lucke, Aleksandar Vakanski, Min Xian

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BI-RADS-NET-V2: A Composite Multi-Task Neural Network for Computer-Aided Diagnosis of Breast Cancer in Ultrasound Images With Semantic and Quantitative Explanations by Boyu Zhang, Aleksandar Vakanski, Min Xian

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Bend-Net: Bending Loss Regularized Multitask Learning Network for Nuclei Segmentation in Histopathology Images by Haotian Wang, Aleksandar Vakanski, Changfa Shi, Min Xian

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Semantic-Aware Adaptive Binary Search for Hard-Label Black-Box Attack by Yiqing Ma, Kyle Lucke, Min Xian, Aleksandar Vakanski

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LASSO–MOGAT: a multi-omics graph attention framework for cancer classification by Fadi Alharbi, Aleksandar Vakanski, Murtada K. Elbashir, Mohanad Mohammed

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A Data Set of Human Body Movements for Physical Rehabilitation Exercises by Aleksandar Vakanski, Hyung-pil Jun, David Paul, Russell Baker

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Comparative Analysis of Multi-Omics Integration Using Graph Neural Networks for Cancer Classification by Fadi Alharbi, Aleksandar Vakanski, Boyu Zhang, Murtada K. Elbashir, Mohanad Mohammed

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Uncertainty quantification in multivariable regression for material property prediction with Bayesian neural networks by Longze Li, Jiang Chang, Aleksandar Vakanski, Yachun Wang, Tiankai Yao, Min Xian

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Dataset of tensile properties for sub-sized specimens of nuclear structural materials by Longze Li, John W. Merickel, Yalei Tang, Rongjie Song, Joshua E. Rittenhouse, Aleksandar Vakanski, Fei Xu

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