Medicaid

Recurrent neural network for predicting absence of heterozygosity from low pass WGS with ultra-low depth.

BACKGROUND: The absence of heterozygosity (AOH) is a kind of genomic change characterized by a long ...

Predicting early mortality and severe intraventricular hemorrhage in very-low birth weight preterm infants: a nationwide, multicenter study using machine learning.

Our aim was to develop a machine learning-based predictor for early mortality and severe intraventri...

Preoperative Differentiation of HER2-Zero and HER2-Low from HER2-Positive Invasive Ductal Breast Cancers Using BI-RADS MRI Features and Machine Learning Modeling.

BACKGROUND: Accurate determination of human epidermal growth factor receptor 2 (HER2) is important f...

Preoperative prediction model for risk of readmission after total joint replacement surgery: a random forest approach leveraging NLP and unfairness mitigation for improved patient care and cost-effectiveness.

BACKGROUND: The Center for Medicare and Medicaid Services (CMS) imposes payment penalties for readmi...

BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management.

BACKGROUND: Low back pain (LBP) is a major global disability contributor with profound health and so...

Evaluation of image quality on low contrast media with deep learning image reconstruction algorithm in prospective ECG-triggering coronary CT angiography.

To assess the impact of low-dose contrast media (CM) injection protocol with deep learning image rec...

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstr...

Deep learning generation of preclinical positron emission tomography (PET) images from low-count PET with task-based performance assessment.

BACKGROUND: Preclinical low-count positron emission tomography (LC-PET) imaging offers numerous adva...

Can oral microbiome predict low birth weight infant delivery?

OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weigh...

Predictive value of magnetic resonance imaging diffusion parameters using artificial intelligence in low-and intermediate-risk prostate cancer patients treated with stereotactic ablative radiotherapy: A pilot study.

INTRODUCTION: To investigate the predictive value of the pre-treatment diffusion parameters of diffu...

[Data-driven intensive care: a lack of comprehensive datasets].

Intensive care units provide a data-rich environment with the potential to generate datasets in the ...

Deep learning for low-data drug discovery: Hurdles and opportunities.

Deep learning is becoming increasingly relevant in drug discovery, from de novo design to protein st...

Improving speech depression detection using transfer learning with wav2vec 2.0 in low-resource environments.

Depression, a pervasive global mental disorder, profoundly impacts daily lives. Despite numerous dee...

Application of machine learning algorithms to identify people with low bone density.

BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individ...

Artificial Intelligence-Assisted Optimization of Antipigmentation Tyrosinase Inhibitors: Molecular Generation Based on a Low Activity Lead Compound.

Artificial intelligence (AI) molecular generation is a highly promising strategy in the drug discov...

Clinical value of deep learning image reconstruction on the diagnosis of pulmonary nodule for ultra-low-dose chest CT imaging.

PURPOSE: To compare the image quality and pulmonary nodule detectability between deep learning image...

Synthetic Low-Energy Monochromatic Image Generation in Single-Energy Computed Tomography System Using a Transformer-Based Deep Learning Model.

While dual-energy computed tomography (DECT) technology introduces energy-specific information in cl...

Pure Vision Transformer (CT-ViT) with Noise2Neighbors Interpolation for Low-Dose CT Image Denoising.

Convolutional neural networks (CNN) have been used for a wide variety of deep learning applications,...

Comment on: "single-port vs multi-port robot-assisted renal surgery: analysis of perioperative outcomes for excision of high and low complexity renal masses".

Mo-fi-disc scoring system: Towards understanding the radiological tools to better delineate the disease process and enhancing our solutions for low back pain in artificial intelligence era.

BACKGROUND: 'Mo-fi-disc' is a new scoring system that quantifies degeneration of the lumbar spine an...

Performance evaluation of deep learning based stream nitrate concentration prediction model to fill stream nitrate data gaps at low-frequency nitrate monitoring basins.

Accurate and frequent nitrate estimates can provide valuable information on the nitrate transport dy...