Surveys

Large language models versus healthcare professionals in providing medical information to patient questions: A systematic review.

OBJECTIVE: The rapid expansion of digital healthcare has heightened the volume of patient communication, thereby increasing the workload for healthcare professionals. Large Language Models (LLMs) hold promises for offering automated responses to patient questions relayed through eHealth platforms, yet concerns persist regarding their effectiveness, accuracy, and limitations in healthcare settings....

Survey on cancer patients' attitudes towards AI and data protection: A cross-sectional study from an Italian cancer center.

Background Artificial Intelligence (AI) is increasingly integrated into oncology, offering opportunities to improve diagnostics, treatment planning, and operational efficiency. However, patient perspectives on AI, especially regarding data protection and ethical implications, remain underexplored. Objective The objective of this study is to investigate cancer patients' attitudes toward the use of ...

RFDNet: Robust Frequency-Based Denoising Network for 3D Ultrasound Vascular Imaging Using a Row-Column Addressed Array.

Three-dimensional (3D) ultrasound vascular imaging (UVI) is essential for visualizing complex vascular structures. Row-column addressed (RCA) arrays, ...

Modelling seizure-related predictors of epilepsy diagnostic gap in two urban informal settlements of Nairobi using machine learning.

BACKGROUND: There is a wide gap in epilepsy diagnosis, particularly in low- and middle-income countries. We used machine learning models to identify s...

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 s...

Letter to the editor regarding "ChatGPT delivers satisfactory responses to the most frequent questions on meniscus surgery".

BACKGROUND: This letter addresses methodological aspects of a study that evaluated a large language model's responses to frequently asked patient ques...

KLiP: A neural network-based surveillance tool for early identification of listening difficulties in children aged 3-6 years.

PURPOSE: To develop and validate a neural network-based Kid's Listening Performance Checklist (KLiP) for early identification of listening difficultie...

Gemini 1.5 Flash provides the most reliable content while ChatGPT-4o offers the highest readability for patient education on meniscal tears.

PURPOSE: The aim of this study was to comparatively evaluate the responses generated by three advanced artificial intelligence (AI) models, ChatGPT-4o...

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...

Early Insights Among Emergency Medicine Physicians on Artificial Intelligence: A National, Convenience-sample Survey of the American College of Emergency Physicians.

OBJECTIVES: This study aimed to assess the current utilization of artificial intelligence (AI) tools among emergency physicians, their attitudes towar...

Evaluating Retrieval-Augmented Generation-Large Language Models for Infective Endocarditis Prophylaxis: Clinical Accuracy and Efficiency.

INTRODUCTION AND AIMS: The use of large language models (LLMs) in healthcare is expanding. Retrieval-augmented generation (RAG) addresses key LLM limi...

Tracking changes in pharmacy students' engagement with ChatGPT: A comparative cross-sectional study (2023-2024).

INTRODUCTION: Since its launch, ChatGPT has generated both interest and concern in education. Between 2023 and 2024, institutional policies shifted fr...

A new approach in autism diagnosis: Evaluating natural interaction using point of view (POV) glasses.

This study introduces an AI-assisted method based on examiner-worn Point of View (POV) glasses and computer vision analysis to provide objective behav...

Methodological Variations in 24-Hour Urine Collection for Nephrolithiasis: A Systematic Review of Reporting Practices and Clinical Implications.

BACKGROUND: A 24-hour urine collection is central to the metabolic evaluation and prevention of nephrolithiasis. Despite its widespread use, methodolo...

An Unsupervised Learning Approach for Multimodal Low Back Pain Stratification.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study proposes a novel stratification framework for individuals with low back pain (LBP). The met...

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...

The use of large language models in clinical documentation: A scoping review.

BACKGROUND: Clinical documentation is essential for safe, high-quality care but has become increasingly complex, contributing to clinician burnout. La...

Artificial intelligence (AI) usage on advanced pharmacy practice experiences.

OBJECTIVE: To determine if pharmacy students are utilizing generative artificial intelligence (AI) on advanced pharmacy practice experiences (APPEs). ...

Real-time highway crash prediction based on SHAP-RFECV and electronic toll collection data: a new feature selection strategy.

Real-time crash prediction has emerged as a critical area of research in traffic safety, aiming to improve safety performance through proactive crash ...

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 ...