This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi+2 more
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Bio-Signal-Guided Robot Adaptive Stiffness Learning via Human-Teleoperated Demonstrations. [PDF]
Xia W, Liao Z, Lu Z, Yao L.
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The Imperative for Hazard- and Place-Specific Assessment of Heat Vulnerability. [PDF]
Karanja J+4 more
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Editorial: Forward and inverse solvers in multi-modal electric and magnetic brain imaging: theory, implementation, and application. [PDF]
Medani T+4 more
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Leveraging In Silico and Artificial Intelligence Models to Advance Drug Disposition and Response Predictions Across the Lifespan. [PDF]
Yang K+4 more
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Understanding Gender-Specific Daily Care Preferences: Topic Modeling Study.
Woo K+7 more
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Predicting the Current and Future Habitat Distribution for an Important Fruit Pest, <i>Grapholita dimorpha</i> Komai (Lepidoptera: Tortricidae), Using an Optimized MaxEnt Model. [PDF]
Huang L+9 more
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Review of Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
Structural Equation Modeling: A Multidisciplinary Journal, 2022Partial Least Squares Structural Equation Modeling (PLSSEM) Using R: A Workbook (Hair et al., 2021) is a workbook based on the textbook: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), (Hair et al., 2017).
Ejike Edeh, WenâJuo Lo, Jam Khojasteh
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The chapters demonstrate two SEM programs with distinct user interfaces and capabilities (Amos and Mplus) with enough specificity that readers can conduct their own analyses without consulting additional resources.
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