Based on this, this study retrospectively analyzes the clinical testing data of patients with diabetic nephropathy and those with simple diabetes mellitus to investigate the predictive value of ...
ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...
Abstract: Traffic flow prediction plays a crucial role in Intelligent Transportation Systems (ITS), as it substantially enhances traffic management efficiency, alleviates congestion, and improves road ...
This repository is for downscaling physical fields using multivariate linear regression. Here the model is applied to downscale significant wave height (SWH) in the Black Sea using low-resolution data ...
Nomograms are superior to traditional multivariate regression models in the competence of quantifying an individual’s personalized risk of having a given condition. To date, no literature has been ...
Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. This work aims to answer three key questions: (1) Can Raman ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Naphthenic acids (NAs) naturally occur in crude oil and its associated produced water, ...
Abstract: The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), ...
Hypertensive disorders of pregnancy (HDP) is a significant cause of maternal and neonatal mortality. This study aims to identify risk factors for new-onset HDP and to develop a prediction model for ...
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