Public Health & Policy

Medicaid

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

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Fuzzy Group Consensus Decision Making and Its Use in Selecting Energy-Saving and Low-carbon Technology Schemes in Star Hotels.

Energy-saving and low-carbon technologies play important roles in reducing environmental risk and de...

Combined Effect of Low-Level Laser Treatment and Levothyroxine on Wound Healing in Rats With Hypothyroidism.

Hypothyroidism delays wound healing by reducing the synthesis of keratinocytes, fibroblast cells, a...

Domain Wall Motion-Based Dual-Threshold Activation Unit for Low-Power Classification of Non-Linearly Separable Functions.

Recently, a great deal of scientific endeavour has been devoted to developing spin-based neuromorphi...

Computational Optics Enables Breast Cancer Profiling in Point-of-Care Settings.

The global burden of cancer, severe diagnostic bottlenecks in underserved regions, and underfunded h...

Low-rank and sparse embedding for dimensionality reduction.

In this paper, we propose a robust subspace learning (SL) framework for dimensionality reduction whi...

Low-rank representation with adaptive graph regularization.

Low-rank representation (LRR) has aroused much attention in the community of data mining. However, i...

Low Protein Z Level: A Thrombophilic Risk Biomarker for Acute Coronary Syndrome.

Acute coronary syndrome (ACS) encompasses a range of thrombotic coronary artery diseases. Protein Z ...

Effect of daily intake of a low-alcohol orange beverage on cardiovascular risk factors in hypercholesterolemic humans.

Oxidative stress, inflammation status, endothelial dysfunction, and imbalanced lipid metabolism play...

3-D Neural denoising for low-dose Coronary CT Angiography (CCTA).

CCTA has become an important tool for coronary arteries assessment in low and medium risk patients. ...

Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks.

Large-scale neural recordings have established that the transformation of sensory stimuli into motor...

Design and Fabrication Technology of Low Profile Tactile Sensor with Digital Interface for Whole Body Robot Skin.

Covering a whole surface of a robot with tiny sensors which can measure local pressure and transmit ...

Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.

Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown...

Using a deep learning network to recognise low back pain in static standing.

Low back pain (LBP) remains one of the most prevalent musculoskeletal disorders, while algorithms th...

Self-supervised sparse coding scheme for image classification based on low rank representation.

Recently, sparse representation, which relies on the underlying assumption that samples can be spars...

Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can r...

Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Traumatically brain injured (TBI) patients are at risk from secondary insults. Arterial hypotension,...

Reliable and Performant Identification of Low-Energy Conformers in the Gas Phase and Water.

Prediction of compound properties from structure via quantitative structure-activity relationship an...

Three-Dimensional Terahertz Coded-Aperture Imaging Based on Matched Filtering and Convolutional Neural Network.

As a promising radar imaging technique, terahertz coded-aperture imaging (TCAI) can achieve high-res...

Deep Convolutional Hashing for Low-Dimensional Binary Embedding of Histopathological Images.

Compact binary representations of histopa-thology images using hashing methods provide efficient app...

Low-Complexity Approximate Convolutional Neural Networks.

In this paper, we present an approach for minimizing the computational complexity of the trained con...

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