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 ...

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 ...

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

The results show that AI adoption leads to significant improvements in ESG scores, with an estimated positive effect of 3.3 ...

Kenya’s food markets are known for extreme volatility influenced by weather shocks, inflation, currency fluctuations, and ...

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

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 ...

Objectives To examine the association between exposure to greenness and hospital admissions for mental disorders, and to ...

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