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1901
Multivariate linear time-series modeling and prediction of cerebral physiologic signals: review of statistical models and implications for human signal analytics
Published 2025-04-01“…The review highlights the clinical implications of using computational models to understand cerebral physiology, while also acknowledging the inherent limitations, including the need for stationary data, challenges with high dimensionality, computational complexity, and limited forecasting horizons.…”
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1902
Perceived risk for screen-detectable cancers among american indian adults in the zuni pueblo, USA: Insights and implications for intervention programs
Published 2025-01-01“…The main objective of this study is to examine factors associated with high perceived cancer risk among Zuni Adults in New Mexico, USA. Methods: We used data from a survey conducted in Zuni Pueblo from October 2020 to April 2021. …”
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A Scoping Review of Corticosterone-Induced Changes in Ionotropic Glutamate Receptor Levels and Localization in the Rodent Brain: Implications for the Auditory System
Published 2025-01-01“…The isolated tissue study did not provide sufficient data for clear conclusions. Conclusions: Variability in experimental models limits our ability to draw definitive conclusions about the effects of CORT on AMPARs across different regions of the nervous system. …”
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1906
Assessing the suitability of the Langevin equation for analyzing measured data through downsampling
Published 2025-01-01“…In such cases, data points often appear as a series of discontinuous jumps, even when the underlying trajectory is continuous. …”
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1907
Evaluation in Our New Normal Environment: Navigating the Challenges with Data Collection
Published 2021-01-01“…For instance, the evaluation budget and time frame both have implications for the quality and type of data that is collected. …”
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Changes of coastline and tidal flat and its implication for ecological protection under human activities: Take China’s Bohai Bay as an example
Published 2024-01-01“…The models used in this paper show a high correlation coefficient between observed and modeling data, which means that this method can be used to predict the changing trend of shoreline and tidal flat. …”
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