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20172024
most citedImproving Mechanical Ventilator Clinical Decision Support Systems with A Machine Learning Classifier for Determining Ventilator Mode

4 citations · 6 across the 7 of their papers we have counts for

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cs.LG2024

MobilityGPT: Enhanced Human Mobility Modeling with a GPT model

Ammar Haydari, Dongjie Chen, Zhengfeng Lai +2

Generative models have shown promising results in capturing human mobility characteristics and generating synthetic trajectories. However, it remains challenging to ensure that the…

cs.LG2023

DPGOMI: Differentially Private Data Publishing with Gaussian Optimized Model Inversion

Dongjie Chen, Sen-ching S. Cheung, Chen-Nee Chuah

High-dimensional data are widely used in the era of deep learning with numerous applications. However, certain data which has sensitive information are not allowed to be shared wit…

cs.LG20231 cited

Benchmarking Adversarial Robustness of Compressed Deep Learning Models

Brijesh Vora, Kartik Patwari, Syed Mahbub Hafiz +2

The increasing size of Deep Neural Networks (DNNs) poses a pressing need for model compression, particularly when employed on resource constrained devices. Concurrently, the suscep…

cs.LG2021

Deep Learning-Based Detection of the Acute Respiratory Distress Syndrome: What Are the Models Learning?

Gregory B. Rehm, Chao Wang, Irene Cortes-Puch +2

The acute respiratory distress syndrome (ARDS) is a severe form of hypoxemic respiratory failure with in-hospital mortality of 35-46%. High mortality is thought to be related in pa…

cs.LG20194 cited

Improving Mechanical Ventilator Clinical Decision Support Systems with A Machine Learning Classifier for Determining Ventilator Mode

Gregory B. Rehm, Brooks T. Kuhn, Jimmy Nguyen +3

Clinical decision support systems (CDSS) will play an in-creasing role in improving the quality of medical care for critically ill patients. However, due to limitations in current…

cs.LG20171 cited

Anomaly Detection in Hierarchical Data Streams under Unknown Models

Sattar Vakili, Qing Zhao, Chang Liu +1

We consider the problem of detecting a few targets among a large number of hierarchical data streams. The data streams are modeled as random processes with unknown and potentially…