| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Müller, Martin
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (38/38 displayed)
- 2024Overview: Machine Learning for Segmentation and Classification of Complex Steel Microstructures
- 2024Efficient Phase Segmentation of Light-Optical Microscopy Images of Highly Complex Microstructures Using a Correlative Approach in Combination with Deep Learning Techniques
- 2023Reproducible Quantification of the Microstructure of Complex Quenched and Quenched and Tempered Steels Using Modern Methods of Machine Learning
- 2023Influence of the Sequence Motive Repeating Number on Protein Folding in Spider Silk Protein Filmscitations
- 2023Klassifizierung komplexer Gefüge mit maschinellem Lernen am Beispiel bainitischer Stähle
- 2022Addressing materials’ microstructure diversity using transfer learningcitations
- 2022Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopycitations
- 2022Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopy
- 2022Addressing materials' microstructure diversity using transfer learningcitations
- 2021High Hydrogen Mobility in an Amide–Borohydride Compound Studied by Quasielastic Neutron Scatteringcitations
- 2021A Complementary and Revised View on the N-Acylation of Chitosan with Hexanoyl Chloride
- 2021Effectiveness and Utility of Virtual Reality Simulation as an Educational Tool for Safe Performance of COVID-19 Diagnostics: Prospective, Randomized Pilot Trialcitations
- 2021Microstructural Classification of Bainitic Subclasses in Low-Carbon Multi-Phase Steels Using Machine Learning Techniques
- 2021A deep learning approach for complex microstructure inferencecitations
- 2021A dangerously underrated entity? Non-specific complaints at emergency department presentation are associated with utilisation of less diagnostic resourcescitations
- 2021Deformation Behavior of Cross-Linked Supercrystalline Nanocompositescitations
- 2020Classification of Bainitic Structures Using Textural Parameters and Machine Learning Techniques
- 2020Towards Quantitative Interpretation of Fourier-Transform Photocurrent Spectroscopy on Thin-Film Solar Cellscitations
- 2020Catechol Containing Polyelectrolyte Complex Nanoparticles as Local Drug Delivery System for Bortezomib at Bone Substitute Materialscitations
- 2019Hierarchical supercrystalline nanocomposites through the self-assembly of organically-modified ceramic nanoparticles
- 2019Hierarchical supercrystalline nanocomposites through the self-assembly of organically-modified ceramic nanoparticlescitations
- 2019Iron oxide-based nanostructured ceramics with tailored magnetic and mechanical properties: Development of mechanically robust, bulk superparamagnetic materials
- 2019Iron oxide-based nanostructured ceramics with tailored magnetic and mechanical properties: development of mechanically robust, bulk superparamagnetic materialscitations
- 2019Modulating the Mechanical Properties of Supercrystalline Nanocomposite Materials via Solvent–Ligand Interactionscitations
- 2018Bioinspired thermoresponsive nanoscaled coatings: Tailor-made polymer brushes with bioconjugated arginine-glycine-aspartic acid-peptidescitations
- 2018Phase Transformations in the Brazing Joint during Transient Liquid Phase Bonding of a γ-TiAl Alloy Studied with In Situ High-Energy X-Ray Diffractioncitations
- 2017Local flow stresses in interpenetrating-phase composites based on nanoporous gold — In situ diffractioncitations
- 2016Local flow stresses in interpenetrating-phase composites based on nanoporous gold — in situ diffraction
- 2016In-situ Observation of Cross-Sectional Microstructural Changes and Stress Distributions in Fracturing TiN Thin Film during Nanoindentationcitations
- 2016Phase Transformation and Residual Stress in a Laser Beam Spot-Welded TiAl-Based Alloycitations
- 2016High-temperature stable Zirconia particles doped with Yttrium, Lanthanum, and Gadoliniumcitations
- 2016In Situ Synchrotron Radiation Diffraction of The Solidificationof Mg-Dy(-Zr) Alloys
- 2015Synthesis and thermal stability of zirconia and yttria-stabilized zirconia microspheres
- 2014Nanocomposite coatings with stimuli-responsive catalytic activitycitations
- 2010Studying the influence of chemical structure on the surface properties of polymer filmscitations
- 2009Charging and structure of zwitterionic supported bilayer lipid membranes studied by streaming current measurements, fluorescence microscopy, and attenuated total reflection Fourier transform infrared spectroscopycitations
- 2001Origin and effect of fiber attack for the processing of C/SiC
- 2001Improving damage tolerance of C/SiC
Places of action
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article
Effectiveness and Utility of Virtual Reality Simulation as an Educational Tool for Safe Performance of COVID-19 Diagnostics: Prospective, Randomized Pilot Trial
Abstract
<jats:sec><jats:title>Background</jats:title><jats:p>Although the proper use of hygiene and personal protective equipment (PPE) is paramount for preventing the spread of diseases such as COVID-19, health care personnel have been shown to use incorrect techniques for donning/doffing of PPE and hand hygiene, leading to a large number of infections among health professionals. Education and training are difficult owing to the social distancing restrictions in place, shortages of PPE and testing material, and lack of evidence on optimal training. Virtual reality (VR) simulation can offer a multisensory, 3-D, fully immersive, and safe training opportunity that addresses these obstacles.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>The aim of this study is to explore the short- and long-term effectiveness of a fully immersive VR simulation versus a traditional learning method regarding a COVID-19–related skill set and media-specific variables influencing training outcomes.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>This was a prospective, randomized controlled pilot study on medical students (N=29; intervention VR training, n=15, vs control video-based instruction, n=14) to compare the performance of hand disinfection, nasopharyngeal swab taking, and donning/doffing of PPE before and after training and 1 month later as well as variables of media use.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Both groups performed significantly better after training, with the effect sustained over one month. After training, the VR group performed significantly better in taking a nasopharyngeal swab, scoring a median of 14 out of 17 points (IQR 13-15) versus 12 out of 17 points (IQR 11-14) in the control group, P=.03. With good immersion and tolerability of the VR simulation, satisfaction was significantly higher in the VR group compared to the control group (median score of User Satisfaction Evaluation Questionnaire 27/30, IQR 23-28, vs 22/30, IQR 20-24, in the control group; P=.01).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>VR simulation was at least as effective as traditional learning methods in training medical students while providing benefits regarding user satisfaction. These results add to the growing body of evidence that VR is a useful tool for acquiring simple and complex clinical skills.</jats:p></jats:sec>