9 citations · 10 across the 9 of their papers we have counts for
10 papers
Blockchains for Internet of Things: Fundamentals, Applications, and Challenges
Yusen Wu, Ye Hu, Mingzhe Chen +2
Internet of Things (IoT) services necessitate the storage, transmission, and analysis of diverse data for inference, autonomy, and control. Blockchains, with their inherent propert…
Improving VTE Identification through Adaptive NLP Model Selection and Clinical Expert Rule-based Classifier from Radiology Reports
Jamie Deng, Yusen Wu, Hilary Hayssen +8
Rapid and accurate identification of Venous thromboembolism (VTE), a severe cardiovascular condition including deep vein thrombosis (DVT) and pulmonary embolism (PE), is important…
Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline for Federated Image Classifications
Yusen Wu, Jamie Deng, Hao Chen +2
Federated Learning (FL) has revolutionized how we train deep neural networks by enabling decentralized collaboration while safeguarding sensitive data and improving model performan…
Soft Merging: A Flexible and Robust Soft Model Merging Approach for Enhanced Neural Network Performance
Hao Chen, Yusen Wu, Phuong Nguyen +2
Stochastic Gradient Descent (SGD), a widely used optimization algorithm in deep learning, is often limited to converging to local optima due to the non-convex nature of the problem…
CCS-GAN: COVID-19 CT-scan classification with very few positive training images
Sumeet Menon, Jayalakshmi Mangalagiri, Josh Galita +7
We present a novel algorithm that is able to classify COVID-19 pneumonia from CT Scan slices using a very small sample of training images exhibiting COVID-19 pneumonia in tandem wi…
Tolerating Adversarial Attacks and Byzantine Faults in Distributed Machine Learning
Yusen Wu, Hao Chen, Xin Wang +3
Adversarial attacks attempt to disrupt the training, retraining and utilizing of artificial intelligence and machine learning models in large-scale distributed machine learning sys…
Toward Generating Synthetic CT Volumes using a 3D-Conditional Generative Adversarial Network
Jayalakshmi Mangalagiri, David Chapman, Aryya Gangopadhyay +7
We present a novel conditional Generative Adversarial Network (cGAN) architecture that is capable of generating 3D Computed Tomography scans in voxels from noisy and/or pixelated a…
Deep Expectation-Maximization for Semi-Supervised Lung Cancer Screening
Sumeet Menon, David Chapman, Phuong Nguyen +3
We present a semi-supervised algorithm for lung cancer screening in which a 3D Convolutional Neural Network (CNN) is trained using the Expectation-Maximization (EM) meta-algorithm.…
Generating Realistic COVID19 X-rays with a Mean Teacher + Transfer Learning GAN
Sumeet Menon, Joshua Galita, David Chapman +7
COVID-19 is a novel infectious disease responsible for over 800K deaths worldwide as of August 2020. The need for rapid testing is a high priority and alternative testing strategie…
Hybrid Mortality Prediction using Multiple Source Systems
Isaac Mativo, Yelena Yesha, Michael Grasso +2
The use of artificial intelligence in clinical care to improve decision support systems is increasing. This is not surprising since, by its very nature, the practice of medicine co…