Health Policy

Providing an accurate global model for monthly solar radiation forecasting using artificial intelligence based on air quality index and meteorological data of different cities worldwide.

This study aims to present an exact model for predicting solar radiation worldwide through a general...

Composited FishNet: Fish Detection and Species Recognition From Low-Quality Underwater Videos.

The automatic detection and identification of fish from underwater videos is of great significance f...

Improvement of image quality for pancreatic cancer using deep learning-generated virtual monochromatic images: Comparison with single-energy computed tomography.

PURPOSE: To construct a deep convolutional neural network that generates virtual monochromatic image...

Robot-assisted minimally invasive transforaminal lumbar interbody fusion versus open transforaminal lumbar interbody fusion: a retrospective matched-control analysis for clinical and quality-of-life outcomes.

To compare the screw accuracy and clinical outcomes between robot-assisted minimally invasive trans...

Artificial intelligence for prediction of measurement-based patient-specific quality assurance is ready for prime time.

The influence of random number generation in dissipative particle dynamics simulations using a cryptographic hash function.

The tiny encryption algorithm (TEA) is widely used when performing dissipative particle dynamics (DP...

Inaccuracies in Google's Health-Based Knowledge Panels Perpetuate Widespread Misconceptions Involving Infectious Disease Transmission.

Google health-based Knowledge Panels were designed to provide users with high-quality basic medical ...

Fp-GAN with Fused Regional Features for the Synthesis of High-Quality Paired Medical Images.

The use of medical image synthesis with generative adversarial networks (GAN) is effective for expan...

Enhancing Graph Neural Networks by a High-quality Aggregation of Beneficial Information.

Graph Neural Networks (GNNs), such as GCN, GraphSAGE, GAT, and SGC, have achieved state-of-the-art p...

Comparison of image quality and lesion diagnosis in abdominopelvic unenhanced CT between reduced-dose CT using deep learning post-processing and standard-dose CT using iterative reconstruction: A prospective study.

PURPOSE: To compare image quality and lesion diagnosis between reduced-dose abdominopelvic unenhance...

Development Issues of Healthcare Robots: Compassionate Communication for Older Adults with Dementia.

Although progress is being made in affective computing, issues remain in enabling the effective expr...

Cancer Classification with a Cost-Sensitive Naive Bayes Stacking Ensemble.

Ensemble learning combines multiple learners to perform combinatorial learning, which has advantages...

Applying Contemporary Machine Learning Approaches to Nutrition Care Real-World Evidence: Findings From the National Quality Improvement Data Set.

Using real-world data from the Academy of Nutrition and Dietetics Health Informatics Infrastructure,...

Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations.

OBJECTIVES: To investigate the image quality and perception of a sinogram-based deep learning image ...

Image Quality Assessment of Fetal Brain MRI Using Multi-Instance Deep Learning Methods.

BACKGROUND: Due to random motion of fetuses and maternal respirations, image quality of fetal brain ...

Deep-learning-based image reconstruction in dynamic contrast-enhanced abdominal CT: image quality and lesion detection among reconstruction strength levels.

AIM: To evaluate the use of deep-learning-based image reconstruction (DLIR) algorithms in dynamic co...

Availability and reporting quality of external validations of machine-learning prediction models with orthopedic surgical outcomes: a systematic review.

Background and purpose - External validation of machine learning (ML) prediction models is an essent...

Data valuation for medical imaging using Shapley value and application to a large-scale chest X-ray dataset.

The reliability of machine learning models can be compromised when trained on low quality data. Many...

Clinically Applicable Machine Learning Approaches to Identify Attributes of Chronic Kidney Disease (CKD) for Use in Low-Cost Diagnostic Screening.

OBJECTIVE: Chronic kidney disease (CKD) is a major public health concern worldwide. High costs of la...

Artificial Intelligence Methods for Rapid Vascular Access Aneurysm Classification in Remote or In-Person Settings.

BACKGROUND: Innovations in artificial intelligence (AI) have proven to be effective contributors to ...

Current Status and Quality of Machine Learning-Based Radiomics Studies for Glioma Grading: A Systematic Review.

INTRODUCTION: Radiomics now has significant momentum in the era of precision medicine. Glioma is one...