Public Health & Policy

Medicaid

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

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Uncovering Predictors of Low Hippocampal Volume: Evidence from a Large-Scale Machine-Learning-Based Study in the UK Biobank.

INTRODUCTION: Hippocampal atrophy is an established biomarker for conversion from the normal ageing ...

Resilience evaluation of low-carbon supply chain based on improved matter-element extension model.

How to evaluate the resilience level and change trend of supply chain is an important research direc...

Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-bas...

Building large-scale registries from unstructured clinical notes using a low-resource natural language processing pipeline.

Building clinical registries is an important step in clinical research and improvement of patient ca...

Encrypted Image Classification with Low Memory Footprint Using Fully Homomorphic Encryption.

Classifying images has become a straightforward and accessible task, thanks to the advent of Deep Ne...

A universal ANN-to-SNN framework for achieving high accuracy and low latency deep Spiking Neural Networks.

Spiking Neural Networks (SNNs) have become one of the most prominent next-generation computational m...

Improved overall image quality in low-dose dual-energy computed tomography enterography using deep-learning image reconstruction.

OBJECTIVE: To demonstrate the clinical advantages of a deep-learning image reconstruction (DLIR) in ...

A comparative evaluation of low-density lipoprotein cholesterol estimation: Machine learning algorithms versus various equations.

BACKGROUND: Given the critical importance of Low-density lipoprotein cholesterol (LDL-C) levels in d...

A Physics-Informed Low-Shot Adversarial Learning for sEMG-Based Estimation of Muscle Force and Joint Kinematics.

Muscle force and joint kinematics estimation from surface electromyography (sEMG) are essential for ...

A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising.

Low-dose computer tomography (LDCT) has been widely used in medical diagnosis. Various denoising met...

Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction.

RATIONALE AND OBJECTIVE: To investigate the influence of the deep learning image reconstruction (DLI...

Deep learning-based harmonization of trabecular bone microstructures between high- and low-resolution CT imaging.

BACKGROUND: Osteoporosis is a bone disease related to increased bone loss and fracture-risk. The var...

Predicting extremely low body weight from 12-lead electrocardiograms using a deep neural network.

Previous studies have successfully predicted overweight status by applying deep learning to 12-lead ...

A novel deep learning-based method for automatic stereology of microglia cells from low magnification images.

Microglial cells mediate diverse homeostatic, inflammatory, and immune processes during normal devel...

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