Surveys

Association of blood urea nitrogen to high-density lipoprotein ratio with all-cause and cardiovascular mortality in individuals with mildly reduced eGFR.

BACKGROUND: Patients with mild-to-moderate renal impairment face elevated cardiovascular risk, yet early detection tools remain limited. The Cardiovascular-Kidney-Metabolism (CKM) interplay underscores the need for integrated biomarkers. The Blood Urea Nitrogen (BUN) to High-Density Lipoprotein (HDL) cholesterol ratio (BUN/HDL) was therefore evaluated for early risk stratification. METHODS: This c...

Hands-on Artificial Intelligence Education for Radiology Residents: A Three-year Feasibility and Curriculum Implementation Study.

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) has rapidly transformed radiology practice, yet structured and practical AI education remains inconsistently integrated into radiology residency training. We developed and implemented a hands-on AI curriculum designed to integrate core computational principles with clinically relevant imaging applications. This study describes the curriculum d...

Steatosis liver index: A validated machine learning model using clinical data distinguishes steatotic liver disease phenotypes.

INTRODUCTION AND OBJECTIVES: Steatotic liver disease (SLD) is a leading cause of liver disease worldwide. Itsstratified into metabolic dysfunction-ass...

From Clinic to Home: Validating the Social Communication Scale for Telemedicine-Supported Early Autism Screening in Chinese Toddlers.

Telemedicine is reshaping how early autism detection can be delivered, particularly in resource-limited settings. Yet, most existing tele-assessment t...

Development and clinical translation of smartphone-based digital biomarkers for Parkinson's disease: a structured review.

Diagnosis of Parkinson's disease (PD) remains a major clinical challenge, particularly in the prodromal and early clinically evident stages, when symp...

An expert-based assessment of the quality, reliability, understandability, and readability of ChatGPT responses on cerebral palsy.

PURPOSE: In recent years, artificial intelligence-based language models have emerged as a means of rapid access to health-related information. This st...

Diagnostic Performance of Machine Learning for Systemic Lupus Erythematosus: Systematic Review and Meta-Analysis.

BACKGROUND: Early and accurate diagnosis of systemic lupus erythematosus (SLE) and its organ involvement is essential. Previous reviews of machine lea...

Alignment Between Large Language Models and Consensus in Endoscopic Spinal Disc Surgery: A Comparative Analysis Against the Neurocore-SENSED.

BACKGROUND: The Neurocore-SENSED framework, derived from a three-round modified Delphi process involving 77 international spine surgeons, provides a s...

Adaptive NLI-Driven Claim Verification with Statistical Decision Modeling for Low-Latency Hallucination Reduction in Large Language Models.

Large Language Models (LLMs) exhibit a critical tendency to generate factually incorrect yet linguistically fluent outputs - a phenomenon termed hallu...

Evaluation of LLMs for Automated Dental-to-Medical Consult Letter Generation: Comparative Study.

INTRODUCTION AND AIMS: For dental patients with systemic diseases, multidisciplinary care via referral letters is essential for clinical safety. This ...

Temporal validation of machine-learning models for shingles vaccine nonvaccination among U.S. adults aged 50 years and older.

BACKGROUND: Herpes zoster vaccination is recommended for U.S. adults aged 50 years and older, yet many remain unvaccinated. Prior National Health Inte...

Peripheral lymphocyte subset profiles associated with Traditional Chinese Medicine constitution in 853 adults: a cross-sectional study.

BACKGROUND: The Traditional Chinese Medicine (TCM) constitution framework classifies adults as Pinghe (balanced constitution) or as having one or more...

Status, challenges, and future directions of machine learning in the management of epilepsy: a systematic review and meta-analysis.

BACKGROUND: Despite advances in epilepsy treatment options, selecting the appropriate therapy for an individual with epilepsy is a process of trial an...

Generative AI emotion recognition from bodily gestures and vocal tone reveals modality-specific performance and positivity bias.

Advances in generative artificial intelligence (GenAI) have prompted interest in its application in sensitive fields, including mental health. Yet the...

A Reliability-Guided Fusion and Dynamic Dual-Domain Mask-Modulated Shearlet Network for Medical Image Segmentation.

Deep learning methods are becoming increasingly important for medical image segmentation. However, previous approaches often performed poorly in spati...

Machine Learning-Based Subtype Classification of Sepsis-Associated Acute Kidney Injury and Differential Responses to Renal Replacement Therapy.

BackgroundSepsis-associated acute kidney injury (SA-AKI) is highly heterogeneous with controversial optimal renal replacement therapy (RRT) strategies...

Toward a future role for liver biopsy in HCC: literature evidence and survey-based perspectives from Korean experts.

The role of liver biopsy in hepatocellular carcinoma (HCC) is being re-evaluated in the era of precision oncology and biomarker-driven systemic therap...

Deceptive bias measurement in deep learning: Assessing shortcut reliance in TCGA cancer models.

Machine learning bias is a persistent challenge because it can create unfair outcomes, limit generalization, and reduce trust in real-world applicatio...

Clinician Perceptions of AI in Care: Cross-Sectional Survey.

BACKGROUND: AI is increasingly being explored as a tool to enhance efficiency, access, and diagnostic accuracy in mental health care. However, the per...

Trust in Artificial Intelligence-Generated Oral Health Information and Its Influence on Patient Decision-Making: A Cross-Sectional Study.

PURPOSE: Artificial intelligence (AI)-assisted applications are increasingly used to obtain health-related information; however, concerns remain regar...