Surveys

Clinical Validation of Apollo™, A Novel Web-Based Tool for Refractive Error Self-Assessment.

Refractive errors are a leading cause of visual impairment, with substantial economic impact. Digital refraction systems may help improve access to eye care, especially for underserved populations. Considering their relevance, this study evaluated the Apollo™, a novel web-based system for self-assessed refractive error measurement, in estimating spherical equivalent (SEQ) compared to manifest refr...

A Randomised Study of ChatGPT-4o vs. Written Materials for Teaching Periodontal-Systemic Relationships in Dental Education.

INTRODUCTION: The bidirectional relationship between periodontal and systemic diseases (particularly diabetes and cardiovascular diseases) is central to contemporary dental curricula. However, the effectiveness of Large Language Model (LLM) tools compared to traditional written materials remains unclear. MATERIALS AND METHODS: In this study, 70 fourth-year dental students were divided into two equ...

Large language models for risk-of-bias assessment in randomised clinical trials-a comparative validation study.

BACKGROUND: Large language models (LLMs) are emerging tools for evidence synthesis. Risk of bias (RoB) assessment of trials remains an essential but t...

Handling Missing Patient-Reported Outcomes in Longitudinal Clinical Trials: A Simulation Study.

OBJECTIVE: To compare the performance of multiple imputation, machine learning methods, and complete case analysis for handling missing data in longit...

Artificial Intelligence and Multiomics Beyond PSA Screening in African and Middle Eastern Prostate Cancer Patients.

Prostate cancer (PCa) remains a major global health burden, with incidence rising as populations age. The molecular, histological, and patient-specifi...

Beyond the Hype: Understanding the Limits, Errors and Risk Areas of Artificial Intelligence in Gastroenterology.

Artificial intelligence (AI) has rapidly expanded across gastroenterology, enabling advances in real-time endoscopic detection, radiologic interpretat...

Artificial intelligence and hearing health: a global evidence review of biases and equity implications for Africa.

Artificial intelligence (AI) is increasingly integrated into audiology and hearing health, yet evidence from across the health sciences shows that AI ...

Classification of narcolepsy type 1 using machine learning on Stanford Cataplexy Questionnaire responses and HLA-DQB1∗06:02.

BACKGROUND: Narcolepsy type 1 (NT1) is characterized by sleepiness, disturbed sleep, and cataplexy-episodes of sudden muscle tone loss triggered by em...

Improving support and self-management of ophthalmic patients using an artificial intelligence health coach.

This study evaluates patient engagement and satisfaction with Everyday Medical Monitoring Ally (E.M.M.A), a purpose-trained artificial intelligence (A...

Etiologic diagnosis of seasonal allergic rhinitis supported by artificial intelligence: the @IT-2020 project.

BACKGROUND: A precise etiological diagnosis of seasonal allergic rhinitis (SAR) is essential for a tailored prescription of its only curative treatmen...

Artificial Intelligence in the Internal Medicine Clerkship: Results of a National Survey.

PURPOSE: Artificial intelligence (AI) in medical education is rapidly evolving. The nascent literature about the use of AI in clerkships is sparse. In...

Deep learning and object detection methods for scoring cell types within the human buccal cell micronucleus and cytome assays for human biomonitoring.

Micronuclei (MN) are critical biomarkers for pathological conditions, yet their manual scoring is inherently laborious and prone to significant intero...

From Digital Data to Psychological Insights: Making Sense of Mobile-Sensing Data through Integrative Preprocessing Pipelines.

Psychological research has long centered around questionnaire assessments, but now digital devices, especially smartphones, enable the collection of r...

Using AI scribes in New Zealand primary care consultations: an exploratory survey.

INTRODUCTION: AI scribes have had a rapid uptake in primary care across New Zealand (NZ). The benefits of this new technology must be weighed against ...

Machine Learning Models Used to Predict Abdominal Aortic Aneurysm Growth and Rupture: A Systematic Review and Critical Appraisal.

BACKGROUND: Abdominal aortic aneurysm (AAA) rupture remains a major cause of mortality, and diameter-based surveillance is an imperfect predictor of r...

Deep convolutional neural networks for age and gender estimation using orthopantomogram images: a systematic review.

OBJECTIVE: The primary goal of this systematic review is to critically analyze and evaluate how effectively deep convolutional neural networks (CNNs) ...

Emotion detection unveiled: A cognitive-computational synthesis of physiological models, machine learning, and datasets.

This comprehensive survey synthesizes state-of-the-art advancements in emotion recognition based on physiological signals, specifically focusing on th...

Clinical Feasibility of Deep Learning Contrast Synthesis From MR Fingerprinting in Knee Osteoarthritis.

BACKGROUND: Magnetic Resonance Fingerprinting (MRF) enables rapid quantitative parameter mapping from which synthetic clinical contrast images can be ...

Influence of computed tomography reconstruction algorithms on coronary artery calcium scores and reader agreement.

BACKGROUND: Coronary artery calcium scoring (CACS) is central to cardiovascular risk stratification. Differences between reconstruction algorithms may...

Prospective Evidence on Artificial Intelligence-Assisted Melanoma Diagnostics: A Systematic Review and Meta-Analysis.

IMPORTANCE: Dermoscopy is a standard of care for melanoma diagnostics, and artificial intelligence (AI) systems are increasingly investigated as decis...