Quantum algorithm for quicker clinical prognostic analysis: an application and experimental study using CT scan images of COVID-19 patients
K Sengupta, PR Srivastava - BMC Medical Informatics and Decision …, 2021 - Springer
Background In medical diagnosis and clinical practice, diagnosing a disease early is crucial
for accurate treatment, lessening the stress on the healthcare system. In medical imaging …
for accurate treatment, lessening the stress on the healthcare system. In medical imaging …
Quantum machine learning architecture for COVID-19 classification based on synthetic data generation using conditional adversarial neural network
Background COVID-19 is a novel virus that affects the upper respiratory tract, as well as the
lungs. The scale of the global COVID-19 pandemic, its spreading rate, and deaths are …
lungs. The scale of the global COVID-19 pandemic, its spreading rate, and deaths are …
COVID-19 outbreak prediction using quantum neural networks
P Kairon, S Bhattacharyya - Intelligence Enabled Research: DoSIER 2020, 2021 - Springer
Artificial intelligence has become an important tool in fight against COVID-19. Machine
learning models for COVID-19 global pandemic predictions have shown a higher accuracy …
learning models for COVID-19 global pandemic predictions have shown a higher accuracy …
Hybrid quantum-classical convolutional neural network model for COVID-19 prediction using chest X-ray images
EH Houssein, Z Abohashima… - Journal of …, 2022 - academic.oup.com
Despite the great efforts to find an effective way for coronavirus disease 2019 (COVID-19)
prediction, the virus nature and mutation represent a critical challenge to diagnose the …
prediction, the virus nature and mutation represent a critical challenge to diagnose the …
A quantum-clustering optimization method for COVID-19 CT scan image segmentation
P Singh, SS Bose - Expert systems with applications, 2021 - Elsevier
Abstract The World Health Organization (WHO) has declared Coronavirus Disease 2019
(COVID-19) as one of the highly contagious diseases and considered this epidemic as a …
(COVID-19) as one of the highly contagious diseases and considered this epidemic as a …
COVID-19 detection on IBM quantum computer with classical-quantum transferlearning
E Acar, I Yilmaz - Turkish Journal of Electrical Engineering …, 2021 - journals.tubitak.gov.tr
Diagnose the infected patient as soon as possible in the coronavirus 2019 (COVID-19)
outbreak which is declared as a pandemic by the world health organization (WHO) is …
outbreak which is declared as a pandemic by the world health organization (WHO) is …
Machine Learning with Quantum Seagull Optimization Model for COVID‐19 Chest X‐Ray Image Classification
Early and accurate detection of COVID‐19 is an essential process to curb the spread of this
deadly disease and its mortality rate. Chest radiology scan is a significant tool for early …
deadly disease and its mortality rate. Chest radiology scan is a significant tool for early …
HQDCNet: hybrid quantum dilated convolution neural network for detecting covid-19 in the context of big data analytics
Medical care services are changing to address problems with the development of big data
frameworks as a result of the widespread use of big data analytics. Covid illness has …
frameworks as a result of the widespread use of big data analytics. Covid illness has …
Enhanced image diagnosing approach in medicine using quantum adaptive machine learning techniques
This research introduces quantum adaptive machine learning (QAML) as an innovative
solution to enhance the processing efficiency of machine learning in medical image …
solution to enhance the processing efficiency of machine learning in medical image …
Machine learning applied to diabetes dataset using Quantum versus Classical computation
D Maheshwari, B Garcia-Zapirain… - … symposium on signal …, 2020 - ieeexplore.ieee.org
This paper presents a Quantum versus classical implemented of Machine learning (ML)
algorithm applied to a diabetes dataset. Diabetes is a Sixth deadliest disease in the world …
algorithm applied to a diabetes dataset. Diabetes is a Sixth deadliest disease in the world …