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Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.

Genet Med

December 2024

Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN. Electronic address:

Purpose: The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance.

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During maritime operations, extreme events such as explosions, grounding, and seal failures can cause water ingress into lubricant compartments, forming oil-water emulsions that significantly affect the lubrication performance of ship stern bearings. Existing studies mainly focus on low water content, with limited exploration of the impact of high water content on lubrication performance. To address this gap, viscosity measurements of oil-water mixtures were conducted, and an emulsification viscosity equation applicable to varying water contents was derived.

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The incident angle of seismic waves influences the dynamic response of rock slopes. However, the relationship between the back-slope effect in strong earthquake areas and the incident angle has not been well-explained. Based on the equivalent nodal force method and the viscoelastic artificial boundary theory, the oblique incidence of seismic P-wave and SV-wave are carried out in FLAC3D software.

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