ThreatsDay Bulletin covers stealthy attack trends, evolving phishing tactics, supply chain risks, and how familiar tools are ...

The idea that quantum computing could transform medical artificial intelligence (AI) has gained momentum in recent years, driven by advances in cloud-accessible quantum platforms and hybrid computing ...

Abstract: This article focuses on an aspect of the optimization of support vector machines (SVMs) by genetic algorithms (GAs), including quantum versions, applied to a sensing system for hand gesture ...

ABSTRACT: Depression is a clinically heterogeneous disorder comprising subtypes such as melancholic, atypical, anxious, and unspecified, each characterized by distinct symptom profiles and treatment ...

Abstract: Recently, there has been growing attention on combining quantum machine learning (QML) with classical deep learning approaches as computational techniques are key to improving the ...

In the first two articles of this series, we introduced the foundations of Quantum Machine Learning (QML) and explored how quantum properties such as superposition and entanglement can enhance machine ...

Quantum Machine Learning (QML) is one of the most promising and rapidly evolving fields at the intersection of artificial intelligence and quantum computing. Artificial intelligence has already ...

Population geneticists increasingly confront a paradox: even with genome-scale datasets and advanced machine learning models, subtle population structure often remains undetected, particularly in ...

This project provides a rigorous and practical benchmark of a Quantum Support Vector Classifier (QSVC) for breast cancer diagnosis. Using the well-known Wisconsin Breast Cancer dataset from ...

A new study suggests that quantum computing could play a decisive role in the escalating arms race between cybersecurity defenders and increasingly sophisticated cyber threats. Researchers from the ...