Latest AI and machine learning research in surveys for healthcare professionals.
This study investigated the sensitivity of event-related potentials (ERP) to factors influencing trust in machine learning (ML) automation, specifically ML reliability, bias, and transparency, with the goal of identifying an electrophysiological marker of trust in automation. Participants performed a flanker task and observed a simulated ML algorithm perform a modified flanker task, while ERP data...
Actuators are to robots what muscles are to humans. They enable motion and determine strength and dexterity. The fiber form factor makes skeletal muscles modular, scalable, and densely integrated (50% of human body weight). In contrast, servo motors that drive today's robots lack the flexibility and modularity of muscle fibers, limiting integration and dexterity. Here, we report electrofluidic fib...
Mental health issues such as stress and anxiety are highly prevalent among university students, often affecting their academic performance and overall...
STATEMENT OF PROBLEM: Cone beam computed tomography (CBCT) scans acquired with interocclusal separation improve stability and reduce motion artifacts ...
The reconstruction of complex networks from time series data has become a common practice in neuroscience and dynamical systems, particularly using sy...
BACKGROUND: Discharge planning (DP) is crucial for care continuity after a hospital stay but remains complex due to organizational constraints, interp...
BACKGROUND: The promise of artificial intelligence (AI) in medicine depends on its ability to learn from data that reflect what matters to patients an...
OBJECTIVE: To improve fairness (reduced disparities across skin tones and sexes) and trust (well-calibrated uncertainty metrics that indicate unreliab...
BACKGROUND: Generative artificial intelligence (AI) tools such as ChatGPT are increasingly used in academic research, yet evidence on postgraduate stu...
BACKGROUND: Successful applications of artificial intelligence (AI) in healthcare have increased interest in how it could be integrated into orthopaed...
BACKGROUND: Effective physician-patient communication is a core component of high-quality medical care, yet it remains challenging to teach and assess...
BACKGROUND: Enhanced Recovery After Surgery (ERAS) pathways improve outcomes after bariatric and gastrointestinal (GI) cancer surgery, yet real-world ...
BACKGROUND: Artificial intelligence (AI) transforms healthcare data collection, analysis, and application, making AI proficiency a growing necessity a...
AIM: The aim of this study is to assess nurse practitioner students' perceptions and engagement with Isabel's artificial intelligence (AI) based diffe...
With the increasing popularity of AI, it is critical to gain an understanding of how academic research ethics are impacted. Unfortunately, in Canada, ...
BACKGROUND: Digital health literacy (DHL) is the ability to locate, understand, evaluate, and apply health information in digital environments. It is ...
BACKGROUND: Conversational artificial intelligence (AI) systems offer potential solutions to traditional constraints in medical consultation skills tr...
Can we train individuals on survey methods to boost their critical processing of public opinion evidence? While polls are one of the most systematic a...
OBJECTIVE: The objective of this review was to systematically evaluate the diagnostic accuracy of artificial intelligence (AI) models for detecting pa...
PURPOSE: To evaluate the reliability and clinical applicability of the three most commonly used large language models (LLMs) (ChatGPT, Gemini, and Cla...