Surveys

Establishing diagnostic thresholds for adult ADHD screening in taxi drivers: validation of the CAARS-S via Item Response Theory and Machine Learning.

BACKGROUND: Adult Attention-Deficit/Hyperactivity Disorder (ADHD) is under-recognized in professional drivers, yet it poses significant safety risks. The Conners' Adult ADHD Rating Scale Short Version (CAARS-S:SV) lacks empirically validated cutoff scores for occupational screening in Iran. This study aimed to assess the psychometric properties of the Persian CAARS-S:SV in taxi drivers and to dete...

Investigating the use, role, and accuracy of generative artificial intelligence in anatomical illustration.

This study investigated the potential role of generative artificial intelligence (Gen AI) in creating and enhancing anatomical illustrations. Human made digital illustrations, Gen AI images created from text prompts, and Gen AI edited versions of the human made illustrations, were shared with staff and students at the University of Dundee with backgrounds in either medicine, dentistry, or anatomy....

Scoring pesticide-likeness of organic compounds via explainable one-class machine learning.

Pesticides, especially eco-friendly biopesticides, are indispensable for crops protection and food security. In this work, we propose a scoring framew...

Reporting of race and ethnicity in studies of artificial intelligence in pediatric urology A secondary analysis of the AI-PEDURO online repository.

INTRODUCTION: While an increasing number of artificial intelligence (AI) models are being developed in pediatric urology, the extent of race/ethnicity...

Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.

Driven by changes in lifestyle and environmental factors, the global incidence of cancer is steadily increasing, which has established it as a leading...

TASRIC: A Type-Aware Semantic Retrieval Augmentation Framework With Iterative Correction for Bias Mitigation.

Gender bias in Chinese natural language processing poses significant challenges due to its high degree of metaphorical expression and strong dependenc...

High-Mobility and Reliability Ultra-Thin-Channel Oxide Semiconductor Field-Effect Transistors for Chip-Interconnect-Embedded Logic and Ferroelectric Memory.

Logic and memory transistors integrated with oxide semiconductors are promising for monolithic 3D systems that enable reconfigurable functionality and...

Bridging the AI chasm in oncology: a standardized platform to enable the in silico clinical validation of AI models within the CHAIMELEON Project.

OBJECTIVE: Artificial intelligence (AI) shows promise for improving cancer management, but clinical adoption is limited by the absence of standardized...

Addressing the Challenges in Using Synthetic Data for Health Research: Application to Cardiology.

Synthetic data offer significant potential for cardiology research by enabling data sharing, preserving privacy, and supporting machine learning model...

DiSCoKit: An open-source toolkit for deploying live LLM experiences in survey research.

In scientific studies of human-AI interaction dynamics, researchers often need to present participants with opportunities to interact with live large-...

Testing standards for AI-based scores in automated essay scoring.

Recent developments in the field of artificial intelligence and machine learning allow the wide application of large language models for the evaluatio...

Attitudes and Usage of ChatGPT Among Medical and Paramedical Students in Iran: A Cross-Sectional Study.

BACKGROUND AND AIMS: ChatGPT, an AI-powered conversational tool, has shown potential to transform healthcare education. However, its integration poses...

Predictors of atrial fibrillation recurrence after catheter ablation: a systematic review.

BACKGROUND: Recurrence of atrial fibrillation (AF) following catheter ablation is a major clinical problem, and there is considerable variability in p...

Three-class obstructive sleep apnea severity assessment: a parallel AHI and ODI explainable artificial intelligence framework using craniofacial-enriched clinical data.

BACKGROUND: Machine learning models for Obstructive Sleep Apnea (OSA) diagnosis have largely inherited some structural limitations: reliance on generi...

Interpretable Machine Learning for Population-Level Tooth Loss Prediction.

Machine learning can support population-level severe tooth loss (STL; ≥6 missing teeth) risk stratification; however, a lack of calibration under doma...

Measuring Consistency Between Large Language Models' Responses to Preventive Care Queries and Official US Preventive Services Task Force (USPSTF) Recommendations: Systematic Test Involving All USPSTF Preventive Care Topics via Simulated User Prompts.

BACKGROUND: Large language models (LLMs) have the potential to provide individualized preventive care guidance at scale. Research, however, has found ...

A Novel Convolutional Neural Network-Based Algorithm for Heart Rate Measurement From Ballistocardiography Signals in Diverse Clinical Settings: Observational Study.

BACKGROUND: Continuous vital sign monitoring ensures early detection, prevents intensive care unit (ICU) admissions, and improves patient outcomes. Co...

Large language models as sources of patient information on robotic knee arthroplasty: a comparative evaluation.

BACKGROUND: Robotic-assisted total knee arthroplasty (rTKA) is increasingly used because of its surgical precision. However, inconsistent outcomes and...

Predicting ACL injury risk in athletes: A systematic review of machine learning-based models.

BACKGROUND: Early ACL injury risk identification in athletes is essential. This systematic review examines machine learning (ML) models for predicting...

Conformal reliability assessment of PPG-based ICU arrhythmia classification under class imbalance and patient heterogeneity.

Deep learning models for photoplethysmography (PPG)-based arrhythmia detection in intensive care are often evaluated by average accuracy, while confor...