Severity: Warning
Message: fopen(/var/lib/php/sessions/ci_session89achg9c0acskm67ac8qpdq2nbm3cmb9): Failed to open stream: No space left on device
Filename: drivers/Session_files_driver.php
Line Number: 177
Backtrace:
File: /var/www/html/index.php
Line: 316
Function: require_once
Severity: Warning
Message: session_start(): Failed to read session data: user (path: /var/lib/php/sessions)
Filename: Session/Session.php
Line Number: 137
Backtrace:
File: /var/www/html/index.php
Line: 316
Function: require_once
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1001/archinternmed.2009.483 | DOI Listing |
Adv Simul (Lond)
December 2024
Harvard Medical School, Boston, USA.
Simulation program staff and leadership often struggle to partner with front-line healthcare workers, their managers, and health system leaders. Simulation-based learning programs are too often seen as burdensome add-ons rather than essential mechanisms supporting clinical workforce readiness. Healthcare system leaders grappling with declining morale, economic pressure, and too few qualified staff often don't see how simulation can help them, and we simulation program leaders can't seem to bridge this gap.
View Article and Find Full Text PDFMachine learning has emerged as a promising approach for predicting molecular properties of proteins, as it addresses limitations of experimental and traditional computational methods. Here, we introduce GSnet, a graph neural network (GNN) trained to predict physicochemical and geometric properties including solvation free energies, diffusion constants, and hydrodynamic radii, based on three-dimensional protein structures. By leveraging transfer learning, pre-trained GSnet embeddings were adapted to predict solvent-accessible surface area (SASA) and residue-specific p values, achieving high accuracy and generalizability.
View Article and Find Full Text PDFAnn Surg Open
December 2024
From the Department of Surgery, NorthShore University Health System, Evanston, IL.
Background: Hernia repairs are one of the most common general surgery procedures and an essential part of training for general surgery residents. The widespread incorporation of robotic hernia repairs warrants the development of a procedure-specific robotic curriculum to assist novice surgeons in improving technical skills.
Objective: To evaluate a robotic hernia simulation-based curriculum for general surgery residents using video review.
Clin Pediatr (Phila)
December 2024
Division of Pediatric Pulmonology, Department of Pediatrics, Emory University, Children's Healthcare of Atlanta, Atlanta, GA, USA.
Tracheostomy-related emergencies (TREs) contribute significantly to preventable mortality. The retention of caregiver knowledge and skills acquired through simulation-based training (SBT) is unknown. This study aimed to assess the management of TREs by caregivers who did and did not receive SBT.
View Article and Find Full Text PDFBMC Med Educ
December 2024
Emergency Medicine Unit and Emergency Medicine Postgraduate Training Program, Department of Internal Medicine, University of Pavia, IRCCS Policlinico San Matteo Foundation, Pavia, Italy.
Background: Despite the importance of Ultrasound-guided Regional Anaesthesia (UGRA) in Emergency Medicine (EM), there is significant variability in UGRA training among emergency physicians. We recently developed a one-day (8 h), simulation-based UGRA course, specifically tailored to help emergency physicians to integrate these skills into their clinical practice.
Methods: In this pre/post intervention study, emergency physicians attended a course consisting of a 4-hour teaching on background knowledge and a practical part structured as follows: a scanning session on a healthy individual; a needling station with an ex-vivo model (turkey thighs); a simulation-based learning experience on local anaesthetic toxicity (LAST); a session on the UGRA simulator BlockSim™.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!