Cultural Competence

Software-based de-filtering restores quantitative accuracy in Clarity2D-enhanced whole-body bone scintigraphy.

OBJECTIVE: To determine whether software-based de-filtering can restore the quantitative accuracy of the bone scan index (BSI) and the number of hot spots (HSn) in whole-body scintigraphy images degraded by the Clarity2D noise-reduction filter. METHODS: In this IRB-approved retrospective study, 101 adults (mean age ± SD: 67 ± 13 years) who underwent 99mTc-HMDP whole-body scintigraphy on a cadmium-...

Between empathy and algorithms: Navigating interpersonal dynamics in AI-augmented mental health care- Discursive review.

The rapid integration of artificial intelligence (AI) into mental health practice presents both unprecedented opportunities and substantial challenges for contemporary care systems. This discursive review critically examines how AI-enabled tools intersect with the interpersonal foundations of psychotherapy, with particular attention to empathy, therapeutic alliance, and relational dynamics. Drawin...

Understanding and Addressing Bias in Artificial Intelligence Systems: A Primer for the Emergency Medicine Physician.

Artificial intelligence (AI) tools and technologies are increasingly being integrated into emergency medicine (EM) practice, not only offering potenti...

Ethical challenges and opportunities for integrating predictive analytics in community-based overdose prevention.

As predictive analytics become more widely integrated into local public health responses to the United States overdose epidemic, community-based subst...

A clinical-AI correlation for integrating artificial intelligence into stroke care: a systematized literature review and practice framework.

BACKGROUND AND PURPOSE: The rapid integration of artificial intelligence (AI) into stroke care has outpaced many clinicians' ability to critically eva...

CHAP: Channel-spatial hierarchical adversarial perturbation for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation (SSMIS) methods predominantly rely on consistency regularization to reinforce invariant feature learning un...

Integrating AI-driven technologies and facial-semantic features for depression detection: A cross-sectional study.

BACKGROUND: Depression is a major global health concern, still individuals with depressive tendencies remain undetected in outpatient settings due to ...

Evolution and design shape protein dynamics in LOV domains - spanning picoseconds to days.

Light-sensitive proteins allow organisms to perceive and respond to their environment, and have diversified over billions of years. Among these, Light...

Artificial Intelligence: Promises and Perils for Employer-Sponsored Mental Health and Well-Being Initiatives.

Artificial intelligence (AI) is reshaping employer-sponsored mental health and well-being initiatives, offering new opportunities for personalized sup...

Supragingival Biomarker flora of Children With and Without Cariogenic Disease and Black Stains, Aged 3 to 6 Years.

BACKGROUND: The oral microbiome plays a pivotal role in the occurrence and progression of dental caries and black stain (BS) pigment. OBJECTIVES: The ...

Leveraging low-cost app-based step count data to assess depression and anxiety in university students: A cross-sectional mobile health study.

BACKGROUND: The prevalence of depression and anxiety among college students worldwide is on the rise, significantly impacting their health and quality...

Efficacy and comparative performance of machine learning models for stroke risk prediction in hypertensive patients: A systematic review and meta-analysis.

BACKGROUND: Stroke poses a significant health burden among hypertensive patients, where traditional risk models often lack precision. Machine learning...

Towards more effective skill discovery in reinforcement learning by incorporating state reachability.

Skill discovery in reinforcement learning seeks to autonomously learn a diverse repertoire of behaviors, enabling efficient adaptation to downstream t...

Unified NDMI for small intestinal cine MRI: repeatability and sensitivity to multicenter variability.

PURPOSE: To establish a comparability-first cine-MRI paradigm for small intestinal motility using a unified, feature-agnostic normalized differential ...

Deep Learning in Vertebral Fracture Detection: Systematic Review and Meta-analysis of Subject- vs. Vertebra-Level Approaches.

RATIONALE AND OBJECTIVES: To provide a context-aware evaluation of deep learning algorithms for vertebral fracture detection by disentangling subject-...

Development and validation of a novel machine learning-based algorithm to predict incident atrial fibrillation: A multicohort analysis.

BACKGROUND: Existing atrial fibrillation (AF) risk prediction models incorporate race as a covariate, systematically underestimating AF risk in black ...

Data Fit for Health Equity: Learning Health Systems, AI, and the STANDING Together Recommendations.

INTRODUCTION: Artificial Intelligence (AI) tools may deliver significant improvements in healthcare and Learning Health Systems are well positioned to...

Can environmental signals influence dietary Behaviours?The impact of governmental green development attention on dietary diversity among older adults.

Against the backdrop of simultaneous national agendas for green transition and healthy ageing, the nutritional behaviour of older adults is being resh...

Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation.

OBJECTIVES: The COVID-19 pandemic has highlighted the growing reliance on machine learning (ML) models for predicting disease severity, which is impor...

Automated Segmentation of Liver and Liver Tumors with SwinUNETR and UNET Neural Networks on 18F-FDG PET/CT.

OBJECTIVES: To develop and evaluate automated segmentation models for the liver and hepatic tumors on 18F-fluorodeoxyglucose positron emission tomogra...