Background: Trainees acquire endoscopic skills at different rates. Fundamental abilities testing could predict the amount of training required to reach a performance goal on a virtual-reality simulator.
Methods: Eleven medical students were tested for fundamental abilities. Baseline endoscopic proficiency was evaluated with the GI Mentor II VR simulator (Simbionix, USA, Cleveland, OH). Subjects trained on the simulator with a defined performance goal. Subjects who achieved the goal were then reassessed.
Results: All subjects completed at least 10 trials or reached the performance goal. The <10 trial group (n=6) tested better for all fundamental abilities and baseline endoscopic performance than the >10 trial group (n=5). The number of trials required to reach the performance goal correlated significantly with both perceptual (r=.92, P=0.001) and visuospatial ability (r=.76, P=.03). Multiple regression showed strong correlation of all three abilities with duration of training (r=.95, P=.015).
Conclusions: Most of the variability in acquisition of endoscopic skills can be accounted for by differences in fundamental abilities of trainees. Testing of fundamental abilities could help identify trainees who will require additional training to achieve desired performance objectives.
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http://dx.doi.org/10.1016/j.amjsurg.2006.03.003 | DOI Listing |
Res Dev Disabil
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Faculty of Pharmaceutical Sciences, Khon Kaen University, Khon Kaen 40002, Thailand.
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Department of Automation, Tsinghua University, Beijing 100084, China.
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Music generation by AI algorithms like Transformer is currently a research hotspot. Existing methods often suffer from issues related to coherence and high computational costs. To address these problems, we propose a novel Transformer-based model that incorporates a gate recurrent unit with root mean square norm restriction (TARREAN).
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Dipartimento di Scienze Farmaceutiche, Università degli Studi di Milano, Via Luigi Mangiagalli, 25, 20133 Milan, Italy.
The widespread emergence of antimicrobial resistance (AMR) is a serious threat to global public health and among Gram-positive cocci, constitutes a priority in the list of AMR-threatening pathogens. To counteract this fundamental problem, the bacterial cell division cycle and the crucial proteins involved in this process emerged as novel attractive targets. FtsZ is an essential cell division protein, and FtsZ inhibitors, especially the benzamide derivatives, have been exploited in the last decade.
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