AI-enabled research tools can accelerate health research, but their data-science roots may clash with epidemiological ...

Background Joint analyses across multiple health datasets can increase statistical power and improve the generalisability of ...

Armed with some Python and a white-hot sense of injustice, one medical student spent six months trying to figure out whether an algorithm trashed his job application.

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...

ABSTRACT: This study investigates the impact of Corporate Social Responsibility (CSR) on financial performance for non-financial firms listed on the Saudi Stock Exchange (Tadawul) from 2016 to 2022, ...

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...

The output variable must be either continuous nature or real value. The output variable has to be a discrete value. The regression algorithm’s task is mapping input value (x) with continuous output ...

ABSTRACT: The multiplicate role of institutional quality in the monetary policy-economic growth nexus from the Ghanaian perspective has remained unexplored. This investigation explores two objectives.

choose a suitable regression model for assessing a specific research hypothesis using data collected from an epidemiological study, fit the model using standard statistical software, evaluate the fit ...

Abstract: Everal real-world classification problems are example-dependent cost-sensitive in nature, where the costs due to misclassification vary between examples. Credit scoring is a typical example ...