Surveys

Task-Based Sampling of Patient Data for Rigorous Machine Learning/AI Performance Assessment.

To assess the performance of an AI algorithm, an independent dataset is needed that matches the intended clinical claim and intended population (e.g., patient characteristics) for which the algorithm is meant. Using all available data for performance assessment may not be practical or optimal; to reduce the risk of sampling bias, the user is expected to utilize training and test data that are repr...

Artificial Intelligence in Military Graduate Medical Education: Trainee Perceptions and Current Use.

ISSUE: Interest in artificial intelligence (AI) has surged recently, with healthcare being no exception. As free, widely accessible AI interfaces grow more user friendly, AI's impact on medical education is likely to be significant. Research into graduate medical education (GME) has explored AI utilization, with strengths noted in diagnostic specialties, but few studies included multiple programs ...

Superior resilience to poisoning and amenability to unlearning in quantum machine learning.

The reliability of artificial intelligence hinges on the integrity of its training data, a foundation often compromised by noise and corruption. Here,...

Deep learning-based HTTP TRACE flood detection in wireless sensor network using deep spectral multi-layer convolutional neural network.

Wireless Sensor Networks (WSN) are widely used across various fields. WSN is composed of many low-cost, high-performance, plug-and-play sensor nodes. ...

Environmental education as a means of combating growing environmental pollution: an optimized- explainable artificial intelligence (XAI) approach.

This work aimed at the use and understanding the impact of education in solving the growing environmental pollution and radiation exposure, which are ...

European Health Care Professionals' Readiness, Benefits, and Ethical Concerns Regarding Generative AI in Continuing Education.

INTRODUCTION: Generative artificial intelligence (GenAI) tools such as ChatGPT are rapidly transforming health care education. Understanding how healt...

Fairness aware subset selection for advancing equity in skin cancer detection.

OBJECTIVES: Skin cancer is the most common malignancy in the United States, with more than five million cases diagnosed annually among 3.3 million ind...

Usability of a deep learning platform for detecting radiographic bone loss and furcation involvement.

BACKGROUND: Assessing radiographic bone condition is important for periodontal diagnosis. The accuracy of radiographic interpretation depends highly o...

Association Between Digital Biomarkers of Health and Anxiety: Systematic Review and Meta-Analysis.

BACKGROUND: Digital biomarkers are gaining interest as proxy markers for mental health, as they enable passive and continuous data collection. However...

Medical Student Experiences With ChatGPT: National Cross-Sectional Study.

BACKGROUND: Artificial intelligence (AI) is increasingly influencing medical student education, with AI-driven chatbots, such as ChatGPT, emerging as ...

Machine learning approaches to identifying neurodevelopmental disorders using social media data: a systematic review.

BACKGROUND: Neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), often eme...

Assessing the integration of digitalization and AI in general medicine curricula in German-speaking Europe: a comprehensive survey.

BACKGROUND: The integration of digitalisation, including artificial intelligence (AI), is becoming increasingly important in healthcare. It is transfo...

Living evidence and gap maps: a scoping review of automation and living mode parameters reported in 44 digital interfaces and their documentation.

OBJECTIVE: To examine how continually updated, living evidence and gap maps (L-EGMs) with an online presence report planned update schedules, retireme...

Machine learning and Regression-Based models for prediction of postoperative atrial fibrillation following coronary artery bypass grafting: A systematic review and meta-analysis.

BACKGROUND: Postoperative atrial fibrillation (POAF) is a common complication following coronary artery bypass grafting (CABG) and is associated with ...

Triage Nurses' Perceptions of Artificial Intelligence: A Cross-Sectional Study.

INTRODUCTION: Emergency department crowding and increasing patient complexity challenge traditional triage models. Artificial intelligence may support...

[Evaluation of Chinese artificial intelligence large language models in oral mucosal disease consultation].

Objective: To investigate the current application status and potential of artificial intelligence (AI) large language models (LLMs) in oral mucosal di...

Effects of Performance and Effort Expectancy on AI-Generated Information Adoption Among Chinese Nursing Professionals: Survey-Based SEM Analysis.

AIM: To examine determinants of nurses' adoption of generative artificial intelligence outputs in clinical practice using a technology acceptance mode...

Attitudes and Knowledge Levels of Optometry Students and Educators Towards Artificial Intelligence in Optometric Practice: An Online Cross-Sectional Survey.

PURPOSE: Artificial intelligence (AI) is poised to revolutionise all aspects of eye care practice in the coming decades. However, not much is known ab...

Trustworthy AI in Digital Health: A Comprehensive Review of Robustness and Explainability.

Ensuring trust in AI systems is essential for the safe and ethical integration of machine learning (ML) systems into high-stakes domains such as digit...

Current State of Artificial Intelligence Adoption and Implementation in Neuroradiology Departments: Insights from a U.S. National Survey.

BACKGROUND AND PURPOSE: Artificial intelligence (AI) is rapidly transforming medical imaging, yet its integration into neuroradiology remains uneven. ...