Most widely cited AI coding benchmarks, including the original SWE-bench, were built primarily around Python repositories, meaning headline performance results may not accurately predict how coding ag ...

While Excel is ubiquitous, I prefer Python for my data analysis. Spreadsheets are great for formatting data, but it's Python that's allowed me to build my own super calculator out of regular Python ...

Abstract: This study evaluates metrics for tasks such as classification, regression, clustering, correlation analysis, statistical tests, segmentation, and image-to-image (I2I) translation in medical ...

ABSTRACT: The rapid proliferation of Internet of Things (IoT) devices in healthcare systems has introduced critical security challenges, particularly in resource-constrained environments typical of ...

Python and R are two of the most popular programming languages used for statistical analysis, data analysis and machine learning. Both languages offer a rich collection of tools and libraries for ...

This repository contains comprehensive implementations and solutions for statistical analysis, data science methodologies, and computational mathematics assignments. Each assignment demonstrates ...

I am a huge fan of Danielle Navarro's book Learning Statistics with R. It is the most accessible statistics book I know of. My students love it. I love it. It's free, and it comes in not only R, but ...

Abstract: Air pollution poses a critical global health challenge requiring accurate prediction systems. This paper evaluates eleven machine learning models for air quality classification using the ...

Stroke is a cerebrovascular illness that brings about the demise of brain tissue. It is the third most prevalent cause of mortality worldwide and a significant contributor to physical impairment.

Compared to cardiac hypertrophy development, much less is known about the molecular mechanisms that mediate hypertrophy regression. One reason for this is that regression in most species occurs slowly ...