Public Health & Policy

Medicaid

Latest AI and machine learning research in medicaid for healthcare professionals.

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Deep learning-enabled accurate normalization of reconstruction kernel effects on emphysema quantification in low-dose CT.

Lung densitometry is being frequently adopted in CT-based emphysema quantification, yet known to be ...

A Low-Cost, Wireless, 3-D-Printed Custom Armband for sEMG Hand Gesture Recognition.

Wearable technology can be employed to elevate the abilities of humans to perform demanding and comp...

Exploring spatiotemporal neural dynamics of the human visual cortex.

The human visual cortex is organized in a hierarchical manner. Although previous evidence supporting...

Parallel imaging and convolutional neural network combined fast MR image reconstruction: Applications in low-latency accelerated real-time imaging.

PURPOSE: To develop and evaluate a parallel imaging and convolutional neural network combined image ...

Ultra-low-dose PET reconstruction using generative adversarial network with feature matching and task-specific perceptual loss.

PURPOSE: Our goal was to use a generative adversarial network (GAN) with feature matching and task-s...

A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.

Manual hand counting of parasites in fecal samples requires costly components and substantial expert...

Multivariate resting-state functional connectivity predicts responses to real and sham acupuncture treatment in chronic low back pain.

Despite the high prevalence and socioeconomic impact of chronic low back pain (cLBP), treatments for...

Robust auto-weighted projective low-rank and sparse recovery for visual representation.

Most existing low-rank and sparse representation models cannot preserve the local manifold structure...

Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes.

Selection hyper-heuristics (HHs) are randomised search methodologies which choose and execute heuris...

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in th...

Low-Rank Deep Convolutional Neural Network for Multitask Learning.

In this paper, we propose a novel multitask learning method based on the deep convolutional network....

Domain Progressive 3D Residual Convolution Network to Improve Low-Dose CT Imaging.

The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a clinical pre...

A Unified Novel Neural Network Approach and a Prototype Hardware Implementation for Ultra-Low Power EEG Classification.

This paper introduces a novel electroencephalogram (EEG) data classification scheme together with it...

Semantic Face Hallucination: Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes.

Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolut...

Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.

PURPOSE: Image-guided radiotherapy provides images not only for patient positioning but also for onl...

Low-Invasive Cell Injection based on Rotational Microrobot.

The advancement of cell injections has created a need for accurate, efficient, and low-invasive inje...

Automated segmentation of 2D low-dose CT images of the psoas-major muscle using deep convolutional neural networks.

The psoas-major muscle has been reported as a predictive factor of sarcopenia. The cross-sectional a...

A deep learning- and partial least square regression-based model observer for a low-contrast lesion detection task in CT.

PURPOSE: This work aims to develop a new framework of image quality assessment using deep learning-b...

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