Most AI coding benchmarks still ask the question: did the agent produce code that passes the current tests? This is a useful ...

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

Background Real-life data is very useful for gaining a better understanding of care in practice and identifying areas for ...

AI systems are getting easier to build, but harder to understand. As outputs become less predictable and workflows more ...

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.

🔍 Motivation: Can we develop deep learning models that efficiently operate on voxel-level fMRI data - just like we do with other medical imaging modalities? 🧠 Architecture: We introduce BrainMT, a ...

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, ...

In many AI applications today, performance is a big deal. You may have noticed that while working with Large Language Models (LLMs), a lot of time is spent waiting—waiting for an API response, waiting ...

ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...

Implement Linear Regression in Python from Scratch ! In this video, we will implement linear regression in python from scratch. We will not use any build in models, but we will understand the code ...