The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

Their study is centred around answering three research questions: Do ANNs perform better than the traditional multiple regression models in the prediction of lighting parameters and energy demand of ...

This study presents valuable findings from a spatiotemporal analysis of arbovirus case notification data from 2013 to 2020 in Brazil, reporting associations between covariates representing potential ...

Existing frameworks like the U.S. Environmental Protection Agency’s Energy Star Portfolio Manager provide useful performance ...

The reduction of health inequalities has been a priority of researchers, decision-makers and practitioners for many years.

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

A 75-year study of 1,497 Michigan lakes finds fish are shrinking, especially the youngest and oldest. Temperature metrics can ...

Background Anti-C1q autoantibodies can disrupt normal complement function, contributing to the formation of pathogenic immune ...

Conclusions: There is a potential mismatch between what clinicians identify as important in determining palliative care need and final eligibility determinations. Patients with dementia were less ...

Hyatt’s technicals maintain its bullish signals after rebounding from its most recent low of $134. It now trades above the 50 ...