Publications by authors named "M C Bialas"

Emergency medicine plays a crucial vital role as the gateway to the Swiss healthcare system. Although it has not yet been officially recognized with a specialist title, unlike most European countries - emergency medicine in Switzerland is characterized by robust research activity. This scientific article demonstrates a dynamic and rigorous evolution.

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Objectives: There is a lack of evidence on whether a grading system or a pass/fail system influences manual skills in dental education. This parallel-group randomized controlled trial aimed to assess the influence of a 15-point grading system compared with a pass/fail evaluation on the quality of orthodontic appliances in dental education.

Methods: Predoctoral dental students of three orthodontic courses (n = 139) were randomly assigned to either the test group (15-point grading system) or the control group (pass/fail) using sealed envelopes.

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This meta-analysis aims to systematically evaluate if different physical activities (PA) improve the social communication impairments (SCI) seen in children with autism spectrum disorder (ASD). For this meta-analysis, five databases (Web of Science, PubMed and Cochrane Library database in English, and CNKI and Wanfang Data Knowledge Service Platform in Chinese) were searched from database inception to September 11, 2024. The eligibility criteria included (1) study population comprised children with ASD, with no gender restriction; (2) experimental group consisted of a PA intervention; (3) control group consisted of nonPA interventions or routine activities; (4) outcomes were assessed using validated SCI scales (e.

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Objective: Manual therapy is a crucial component in rehabilitation education, yet there is a lack of models for evaluating learning in this area. This study aims to develop a foundational evaluation model for manual therapy learning among rehabilitation students, based on the Delphi method, and to analyze the theoretical basis and practical significance of this model.

Methods: An initial framework for evaluating the fundamentals of manual therapy learning was constructed through a literature review and theoretical analysis.

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This article investigates the application of spiking neural networks (SNNs) to the problem of topic modeling (TM): the identification of significant groups of words that represent human-understandable topics in large sets of documents. Our research is based on the hypothesis that an SNN that implements the Hebbian learning paradigm is capable of becoming specialized in the detection of statistically significant word patterns in the presence of adequately tailored sequential input. To support this hypothesis, we propose a novel spiking topic model (STM) that transforms text into a sequence of spikes and uses that sequence to train single-layer SNNs.

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