82 research outputs found

    Evaluation of a new virtual-reality training simulator for hysteroscopy

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    Background: To determine realism and training capacity of HystSim, a new virtual-reality simulator for the training of hysteroscopic interventions. Methods: Sixty-two gynaecological surgeons with various levels of expertise were interviewed at the 13th Practical Course in Gynaecologic Endoscopy in Davos, Switzerland. All participants received a 20-min hands-on training on the simulator and filled out a four-page questionnaire. Twenty-three questions with respect to the realism of the simulation and the training capacity were answered on a seven-point Likert scale along with 11 agree-disagree statements concerning the HystSim training in general. Results: Twenty-six participants had performed more than 50 hysteroscopies ("experts”) and 36 equal to or fewer than 50 ("novices”). Four of 60 (6.6%) responding participants judged the overall impression as "7 - absolutely realistic”, 40 (66.6%) as "6 - realistic”, and 16 (26.6%) as "5 - somewhat realistic”. Novices (6.48; 95% confidence interval [CI] 6.28-6.7) rated the overall training capacity significantly higher than experts (6.08; 95% CI 5.85-6.3), however, high-grade acceptance was found in both groups. In response to the statements, 95.2% believe that HystSim allows procedural training of diagnostic and therapeutic hysteroscopy, and 85.5% suggest that HystSim training should be offered to all novices before performing surgery on real patients. Conclusion: Face validity has been established for a new hysteroscopic surgery simulator. Potential trainees and trainers assess it to be a realistic and useful tool for the training of hysteroscopy. Further systematic validation studies are needed to clarify how this system can be optimally integrated into the gynaecological curriculu

    Evaluation of a new virtual-reality training simulator for hysteroscopy

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    BACKGROUND: To determine realism and training capacity of HystSim, a new virtual-reality simulator for the training of hysteroscopic interventions. METHODS: Sixty-two gynaecological surgeons with various levels of expertise were interviewed at the 13(th) Practical Course in Gynaecologic Endoscopy in Davos, Switzerland. All participants received a 20-min hands-on training on the simulator and filled out a four-page questionnaire. Twenty-three questions with respect to the realism of the simulation and the training capacity were answered on a seven-point Likert scale along with 11 agree-disagree statements concerning the HystSim training in general. RESULTS: Twenty-six participants had performed more than 50 hysteroscopies ("experts") and 36 equal to or fewer than 50 ("novices"). Four of 60 (6.6%) responding participants judged the overall impression as "7 - absolutely realistic", 40 (66.6%) as "6 - realistic", and 16 (26.6%) as "5 - somewhat realistic". Novices (6.48; 95% confidence interval [CI] 6.28-6.7) rated the overall training capacity significantly higher than experts (6.08; 95% CI 5.85-6.3), however, high-grade acceptance was found in both groups. In response to the statements, 95.2% believe that HystSim allows procedural training of diagnostic and therapeutic hysteroscopy, and 85.5% suggest that HystSim training should be offered to all novices before performing surgery on real patients. CONCLUSION: Face validity has been established for a new hysteroscopic surgery simulator. Potential trainees and trainers assess it to be a realistic and useful tool for the training of hysteroscopy. Further systematic validation studies are needed to clarify how this system can be optimally integrated into the gynaecological curriculum

    First results from the AugerPrime Radio Detector

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    Update of the Offline Framework for AugerPrime

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    Outreach activities at the Pierre Auger Observatory

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    The ultra-high-energy cosmic-ray sky above 32 EeV viewed from the Pierre Auger Observatory

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    Event-by-event reconstruction of the shower maximum XmaxX_{\mathrm{max}} with the Surface Detector of the Pierre Auger Observatory using deep learning

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    Reconstruction of Events Recorded with the Water-Cherenkov and Scintillator Surface Detectors of the Pierre Auger Observatory

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    Status and performance of the underground muon detector of the Pierre Auger Observatory

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    The XY Scanner - A Versatile Method of the Absolute End-to-End Calibration of Fluorescence Detectors

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