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Objectives: Research questions about how and why health trends differ between populations require decisions about data analytic procedure. The objective was to document and compare the information returned from stratified, fixed effect and random effect approaches to data modelling for two prototypical descriptive research questions about comparative trends in toothbrushing.

Methods: Data included five cycles of the Health Behaviour in School-aged Children 2006 to 2022, which provided a sample of 980192 11- to 15- year olds from 35 countries.

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Evidence suggests that attenuated mismatch negative (MMN) waves have a close link to auditory verbal hallucinations (AVH) and their clinical outcomes, especially impaired neural oscillations such as θ, β representing attentional control. In current study, thirty patients with schizophrenia and AVH (SZ) and twenty-nine healthy controls (HC) underwent multi-feature MMN paradigm measurements including frequency and duration deviant stimuli (fMMN and dMMN). Clinical symptoms and MMN paradigm were followed up among SZ group after 8-week treatment.

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A novel machine learning based framework for developing composite digital biomarkers of disease progression.

Front Digit Health

January 2025

Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ, United States.

Background: Current methods of measuring disease progression of neurodegenerative disorders, including Parkinson's disease (PD), largely rely on composite clinical rating scales, which are prone to subjective biases and lack the sensitivity to detect progression signals in a timely manner. Digital health technology (DHT)-derived measures offer potential solutions to provide objective, precise, and sensitive measures that address these limitations. However, the complexity of DHT datasets and the potential to derive numerous digital features that were not previously possible to measure pose challenges, including in selection of the most important digital features and construction of composite digital biomarkers.

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Pulse approach: a physics-guided machine learning model for thermal analysis in laser-based powder bed fusion of metals.

Prog Addit Manuf

July 2024

Empa Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, 8600 Dübendorf, Switzerland.

Fast and accurate representation of heat transfer in laser powder-bed fusion of metals (PBF-LB/M) is essential for thermo-mechanical analyses. As an example, it benefits the detection of thermal hotspots at the design stage. While traditional physics-based numerical approaches such as the finite element (FE) method are applicable to a wide variety of problems, they are computationally too expensive for PBF-LB/M due to the space- and time-discretization requirements.

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In this bibliometric analysis, the authors analyze the top 100 (T100) most cited articles on cosmetic upper facial plastic surgery. Throughout this study, the objective of the authors is to delineate the trends in cosmetic upper facial surgeries to identify prevailing techniques, emerging trends, and potential areas of future investigation. The articles were indexed from the Web of Science database and were extracted in a double-blinded manner by 2 independent graders.

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