Objective To clarify whether atherogenic index of plasma (AIP), a comprehensive indicator reflecting both the protective and ...

A research team has developed advanced methodologies for predicting the aboveground biomass (AGB) of corn by integrating unmanned aerial vehicles (UAVs), multi-sensor data, and machine learning models ...

Objective To characterise the use of the prostate specific antigen (PSA) test in primary care in England. Design Population based open cohort study. Setting England. Participants 10 235 805 male ...

A hybrid fuzzy neural network model enhances prediction accuracy of hardness properties in high-performance concrete, ...

Learn what residual standard deviation is, how to calculate it in regression analysis, and why it's crucial for measuring predictability and goodness-of-fit in data modeling.

This important study used five metrics to compare the cost-effectiveness of intramural and extramural research funded by the National Institutes of Health in the United States between 2009 and 2019.

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Standard linear regression predicts a single numeric value ...

Abstract: This paper presents a comprehensive exploration of earthquake magnitude and depth prediction using an advanced machine learning model and multiple linear regression model. The study ...

Abstract: This paper systematically analyzes the market dynamics of the pet industry in China and globally based on multiple linear regression and ARIMA models. First, for the Chinese market, this ...

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