In this investigation, a quantitative structure-property relationship (QSPR) model coupled
with a quantum neural network (QNN) was used to explore the corrosion inhibition efficiency …

This investigation employs a quantum neural network (QNN) synergistically integrated with a
quantitative structure-property relationship (QSPR) model for the comprehensive evaluation …

This study evaluates the efficacy of quantum machine learning (QML) models in predicting
stainless steel corrosion behaviour. Using two datasets, the quantum support vector …

This work used a variational quantum circuit (VQC) in conjunction with a quantitative
structure-property relationship (QSPR) model to completely investigate the corrosion …

This research is the first of its kind to leverage the power of Quantum Machine Learning
(QML) to perform multi-class classification of Cardiovascular Diseases (CVDs). We propose …

This study aims to develop a Quantum Support Vector Classifier (QSVC) model to predict the
structure of ABO3 perovskite accurately. The QSVC model was trained using the Synthetic …

The early detection and accurate diagnosis of cardiovascular diseases is vital to reduce
global morbidity and death rates. In this work, the quantum-inspired seagull optimization …

Accurate early identification and treatment of cardiovascular diseases can prevent heart
failure problems and reduce mortality rates. This study aims to use quantum learning to …

Heart failure is a leading cause of death among people worldwide. The cost of treatment can
be prohibitive, and early prediction of heart failure would reduce treatment costs to patients …

The primary issue of global health today is Cardio-vascular diseases (CVDs) and thus
requires accurate predictive models for detecting it early. Quantum technology combined …