I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to ...

Multicollinearity is a common issue in multiple regression analysis, where the presence of high correlation among predictor ...

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

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

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

Background Although voting is recognised as a social determinant of health, the association between electoral participation ...

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 ...

Background Smoke-free and aerosol-free households (SAFHs) reduce exposure to secondhand smoke and aerosol and support ...

Background Stroke after transcatheter aortic valve implantation (TAVI) is an infrequent but serious complication with ...

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...

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 ...