Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

Abstract: The identification of fraud, waste, and abuse in healthcare systems is critical to minimise financial losses incurred by medical aid companies. Traditional fraud detection methods are based ...

Overview:Machine learning bootcamps focus on deployment workflows and project-based learning outcomes.IIT and global programs provide flexible formats for appli ...

The University of North Texas (UNT) is stepping into the future with a new undergraduate major in Artificial Intelligence (AI), ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

AI is searching particle colliders for the unexpected ...

Dinosaur footprints are iconic fossils, but it is challenging to identify their makers. This is illustrated by a long-standing debate about whether some footprints from the Late Triassic-Early ...

Abstract: Floods are dangerous natural events that can cause massive damage to people and property. This project uses machine learning (ML) methods to predict the chances of flooding by studying ...

This repository contains the official PyTorch implementation of the research paper Unsupervised Multimodal Clustering for Semantics Discovery in Multimodal Utterances ...

Introduction: Cardiogenic shock (CS) is a heterogeneous clinical syndrome, with varied clinical outcomes driven by hemodynamic states, and initial presentation. However, unsupervised machine learning ...

ArticleOctober 24, 2025 Accessing the Differential Suitability of Ganga River Water for Drinking, Irrigation, and Industrial Use: A First-Time Report Based on Index Analysis and Unsupervised Machine ...