Medicaid

LOW CERTAINTY OF EVIDENCE SUPPORTS THE APPLICATION OF (AI) FOR THE AUTOMATIC DETECTION OF CEPHALOMETRIC LANDMARKS WITH PROSPECTS FOR IMPROVEMENTS.

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Artificial Intelligence for Detecting Cephalometric Lan...

Short-term and long-term efficacy in robot-assisted treatment for mid and low rectal cancer: a systematic review and meta-analysis.

OBJECTIVE: This study aims to conduct a meta-analysis to evaluate the short-term and long-term thera...

Evaluation of different feedback designs for target guidance in human controlled robotic cranes: A comparison between high and low performance groups.

Labour shortages and costly operator training are driving the need for digital on-board robotic cran...

Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model.

PURPOSE: Computed tomography (CT) scans are a significant source of medically induced radiation expo...

Food protein-induced allergic proctocolitis in infants is associated with low serum levels of macrophage inflammatory protein-3a.

BACKGROUND: Food protein-induced allergic proctocolitis (FPIAP) is a nonimmunoglobulin (IgE)-mediate...

Learnable PM diffusion coefficients and reformative coordinate attention network for low dose CT denoising.

Various deep learning methods have recently been used for low dose CT (LDCT) denoising. Aggressive d...

Two-surgeon dual-console robotic low anterior resection with selective lateral lymph node dissection-a video vignette.

Submicron- and nanoplastic detection at low micro- to nanogram concentrations using gold nanostar-based surface-enhanced Raman scattering (SERS) substrates.

The presence of submicron- (1 μm-100 nm) and nanoplastic (<100 nm) particles within various sample m...

Risk Factors for Developing Low Estimated Glomerular Filtration Rate and Albuminuria in Living Kidney Donors.

RATIONALE & OBJECTIVE: Chronic kidney disease is associated with significant morbidity and mortality...

Long-term effects of deep-learning digital therapeutics on pain, movement control, and preliminary cost-effectiveness in low back pain: A randomized controlled trial.

OBJECTIVE: The present study aimed to compare the effects of a deep learning-based digital applicati...

Autoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics.

The ability to effectively represent microbiome dynamics is a crucial challenge in their quantitativ...

DTLR-CS: Deep tensor low rank channel cross fusion neural network for reproductive cell segmentation.

In recent years, with the development of deep learning technology, deep neural networks have been wi...

Simultaneous Quantitative Determination of Low-Concentration Preservatives and Heavy Metals in Tricholoma Matsutakes Based on SERS and FLU Spectral Data Fusion.

As an ingredient of great economic value, Tricholoma matsutake has received widespread attention. Ho...

: a novel automated system for malaria diagnosis by using artificial intelligence tools and a universal low-cost robotized microscope.

INTRODUCTION: Malaria is one of the most prevalent infectious diseases in sub-Saharan Africa, with 2...

Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction.

In recent years, the growing awareness of public health has brought attention to low-dose computed t...

Machine learning-based approach for predicting low birth weight.

BACKGROUND: Low birth weight (LBW) has been linked to infant mortality. Predicting LBW is a valuable...

Utilizing deep learning techniques to improve image quality and noise reduction in preclinical low-dose PET images in the sinogram domain.

BACKGROUND: Low-dose positron emission tomography (LD-PET) imaging is commonly employed in preclinic...

Convolutional neural network-based kidney volume estimation from low-dose unenhanced computed tomography scans.

PURPOSE: Kidney volume is important in the management of renal diseases. Unfortunately, the currentl...

A multi-centric evaluation of self-learning GAN based pseudo-CT generation software for low field pelvic magnetic resonance imaging.

PURPOSE/OBJECTIVES: An artificial intelligence-based pseudo-CT from low-field MR images is proposed ...

A bidirectional thermal sensory leaky integrate-and-fire (LIF) neuron model based on bipolar NbO volatile threshold devices with ultra-low operating current.

Brain-like artificial intelligence (AI) will become the main form and important platform in future c...

Rapid analysis of hydrogen cyanide in fresh cassava roots using NIRSand machine learning algorithms: Meeting end user demand for low cyanogenic cassava.

This study focuses on meeting end-users' demand for cassava (Manihot esculenta Crantz) varieties wit...