Frontiers

Soft Computing and Machine Learning Applications for Healthcare Systems

Soft Computing (SC) is an Artificial Intelligence (AI) approach that is more effective at solving real-life problems than traditional computing models. Soft Computing models are tolerant of partial ...
IEEE

Hybrid Deep Learning Models for Enhanced Classification of Phase-Resolved Partial Discharge Patterns From High-Voltage Rotating Machine Insulation

Abstract: Partial discharge (PD) monitoring plays a crucial role in identifying insulation defects in high-voltage rotating machinery, where accurate classification is essential for improving the ...
Devdiscourse

Why AI systems struggle with identities that resist fixed labels

A new academic study argues that the structural reliance of artificial intelligence (AI) systems on classification models creates significant challenges when AI systems attempt to represent fluid and ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...
Chicago Sun-Times

'The ghost in the machine is just us' — AI pinch hits. But there's a problem...

Why are we asking for donations? Why are we asking for donations? This site is free thanks to our community of supporters. Voluntary donations from readers like you keep our news accessible for ...
IEEE

A Topical Review of Quantum and Classical Machine Learning Approaches to Disaster Escape Routing Problems

Abstract: The pathfinding problem in a graph has been solved using several classical algorithms, notably Dijkstra’s and A* algorithms. However, most classical algorithms are most effective on static ...