AIMC Topic: Cross-Over Studies
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What device should be used for telementoring? Randomized controlled trial.
International journal of medical informatics
May 22, 2015
BACKGROUND AND OBJECTIVE: The paper analyzes behavioral patterns of mentors while using different mentoring devices to demonstrate the feasibility of multi-platform mentoring. The fundamental differences of devices supporting telementoring create thr...
Comparison of Coopdech®, CoPilot®, Intubrite®, and Macintosh laryngoscopes for tracheal intubation during pediatric cardiopulmonary resuscitation: a randomized, controlled crossover simulation trial.
European journal of pediatrics
May 21, 2015
UNLABELLED: The aim of the study was to compare the intubation times and success rates of various laryngoscopes during resuscitation in pediatric emergency intubation with uninterrupted chest compression on a standardized pediatric manikin model. Thi...
Does Robotic Telerounding Enhance Nurse-Physician Collaboration Satisfaction About Care Decisions?
Telemedicine journal and e-health : the official journal of the American Telemedicine Association
May 4, 2015
BACKGROUND: Delivering healthcare using remote robotic telepresence is an evolving practice in medical and surgical intensive critical care units and will likely have varied implications for work practices and working relationships in intensive care ...
Conventional Laparoscopic vs Robotic Training: Which is Better for Naive Users? A Randomized Prospective Crossover Study.
Journal of surgical education
Feb 14, 2015
OBJECTIVE: Robotic training (RT) using the da Vinci skills simulator and conventional training (CT) using a laparoscopic "training box" are both used to augment operative skills in minimally invasive surgery. The current study tests the hypothesis th...
Effect of Deep Learning-Based Artificial Intelligence on Radiologists' Performance in Identifying Nigrosome 1 Abnormalities on Susceptibility Map-Weighted Imaging.
Korean journal of radiology
Aug 1, 2025
OBJECTIVE: To evaluate the effect of deep learning (DL)-based artificial intelligence (AI) software on the diagnostic performance of radiologists with different experience levels in detecting nigrosome 1 (N1) abnormalities on susceptibility map-weigh...
Artificial intelligence driven 3D reconstruction for enhanced lung surgery planning.
Nature communications
May 1, 2025
The increasing complexity of lung surgeries necessitates the need for enhanced imaging support to improve the precision and efficiency of preoperative planning. Despite the promise of 3D reconstruction, clinical adoption remains limited due to time c...
Development and Validation of a Sham-AI Model for Intracranial Aneurysm Detection at CT Angiography.
Radiology. Artificial intelligence
May 1, 2025
Purpose To evaluate a sham-artificial intelligence (AI) model acting as a placebo control for a standard-AI model for diagnosis of intracranial aneurysm. Materials and Methods This retrospective crossover, blinded, multireader, multicase study was co...
Utility of AI digital pathology as an aid for pathologists scoring fibrosis in MASH.
Journal of hepatology
May 1, 2025
BACKGROUND & AIMS: Intra and inter-pathologist variability poses a significant challenge in metabolic dysfunction-associated steatohepatitis (MASH) biopsy evaluation, leading to suboptimal selection of patients and confounded assessment of histologic...
Cathodal Transcranial Direct Current Stimulation Does Not Change Implicit Associations Against Alcohol in Alcohol Use Disorder: A Preregistered Clinical Trial.
Addiction biology
Mar 1, 2025
Addictive behaviour is shaped by the dynamic interaction of implicit, bottom-up and explicit, top-down cognitive processes. In alcohol use disorder (AUD), implicit alcohol-related associations have been shown to predict increased subsequent alcohol c...
Performance on Activities of Daily Living and User Experience When Using Artificial Intelligence by Individuals With Vision Impairment.
Translational vision science & technology
Jan 2, 2025
PURPOSE: This study assessed objective performance, usability, and acceptance of artificial intelligence (AI) by people with vision impairment. The goal was to provide evidence-based data to enhance technology selection for people with vision loss (P...
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