US Health Policy

Unraveling soil salinity on potentially toxic element accumulation in coastal Phragmites australis: A novel integration of multivariate and interpretable machine-learning models.

Revealing the key mechanisms influencing the behavior of potentially toxic elements (PTEs) in soil-plant systems is of great significance for environmental protection and grassland development in coastal areas. This study utilized redundancy analysis to assess the effects of soil environmental variables on the concentrations and enrichment of various PTEs in the advantageous forage species Phragmi...

Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk.

In fast-paced urban environments, Citywalk has emerged as a key leisure activity for urban residents to alleviate stress and enhance emotional well-being. From the perspective of virtual-physical interaction, this study integrates social media data with geospatial information, utilizing machine learning methods and spatial statistical analysis to explore the multidimensional driving mechanisms and...

Sweet pepper yield modeling via deep learning and selection of superior genotypes using GBLUP and MGIDI.

Intelligent knowledge about Capsicum annuum L. germplasm could lead to effective management of germplasm. Here, 29 accessions of sweet pepper were inv...

Using fuzzy decision support to create a positive mental health environment for preschoolers.

The preschool period is a crucial time for behavioural and social-emotional development and the cultivation of mental well-being. Preschoolers may be ...

Prediction of Clavien Dindo Classification ≥ Grade III Complications After Epithelial Ovarian Cancer Surgery Using Machine Learning Methods.

Ovarian cancer surgery requires multiple radical resections with a high risk of complications. The aim of this single-centre, retrospective study was...

Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.

BACKGROUND: The last decade has witnessed major advances in the development of artificial intelligence (AI) technologies for use in health care. One o...

An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia.

As per the World Health Organization (WHO), the justifications of people with disabilities globally are restricted by physical and social barriers tha...

Machine learning prediction of right ventricular volume and ejection fraction from two-dimensional echocardiography in patients with pulmonary regurgitation.

Right ventricular (RV) end-diastolic volume (RVEDV) and ejection fraction (RVEF) by cardiac MRI (cMRI) guide management in chronic pulmonary regurgita...

Forecasting trends of rising emergency department chest imaging using machine learning.

INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medi...

AI anxiety and knowledge payment: the roles of perceived value and self-efficacy.

BACKGROUND: The integration of Artificial Intelligence (AI) into daily life raises significant challenges and uncertainties, notably concerning job se...

Assessments of lung nodules by an artificial intelligence chatbot using longitudinal CT images.

Large language models have shown efficacy across multiple medical tasks. However, their value in the assessment of longitudinal follow-up computed tom...

Quantitative analysis and evaluation of winter and summer landscape colors in the Yangzhou ancient Canal utilizing deep learning.

Color is an important index for human visual evaluation of landscape, and it is also a key factor affecting people's recognition and experience of her...

Social media content and suicidality: Implications for practice.

Artificial intelligence is a useful tool for examining suicidality on social media, where people share their thoughts. However, existing research has ...

Predicting mental health disparities using machine learning for African Americans in Southeastern Virginia.

This study examined mental health disparities among African Americans using AI and machine learning for outcome prediction. Analyzing data from Africa...

A practical deep learning model for core temperature prediction of specialized workers in high-temperature environments.

The health issues of hazardous operations in high-temperature environments are increasing concerns to the public, especially since global warming and ...

Projections of single-level indirect lumbar interbody fusion volume and associated costs for Medicare patients to 2050.

BACKGROUND: Anterior, Oblique, and Lateral Lumbar Interbody Fusions (ALIF/OLIF/LLIF) are powerful modalities for achieving indirect decompression of l...

Machine Learning Approach to Identifying Wrong-Site Surgeries Using Centers for Medicare and Medicaid Services Dataset: Development and Validation Study.

BACKGROUND: Wrong-site surgery (WSS) is a critical but preventable medical error, often resulting in severe patient harm and substantial financial cos...

Automatic segmentation of MRI images for brain radiotherapy planning using deep ensemble learning.

This study aimed to develop and evaluate an efficient method to automatically segment T1- and T2-weighted brain magnetic resonance imaging (MRI) image...

Optimizing the value of bioinks and robotics to advance in vivo bioprinting.

In vivo bioprinting strategies aim at facilitating immediate integration of engineered tissues with the host's biological system. As integral parts of...

Bridging MRI Cross-Modality Synthesis and Multi-Contrast Super-Resolution by Fine-Grained Difference Learning.

In multi-modal magnetic resonance imaging (MRI), the tasks of imputing or reconstructing the target modality share a common obstacle: the accurate mod...