Hybrid quantum image classification and federated learning for hepatic steatosis diagnosis
L Lusnig, A Sagingalieva, M Surmach, T Protasevich… - Diagnostics, 2024 - mdpi.com
In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial.
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …
Enhancing TNM Staging in Breast Cancer: A Hybrid Approach with CNN, Edge Detection, and Self-Organizing Maps for Improved Accuracy
Breast cancer remains a leading cause of mortality among women globally, underscoring
the urgent need for improved diagnostic and staging techniques to enhance patient …
the urgent need for improved diagnostic and staging techniques to enhance patient …
Mobile Diagnosis of COVID-19 by Biogeography-based Optimization-guided CNN
X Han, Z Hu - Mobile Networks and Applications, 2024 - Springer
Abstract Since 2019, COVID-19 has profoundly impacted human health around the world.
COVID-19 is extremely contagious, so fast automated diagnosis is necessary. In the field of …
COVID-19 is extremely contagious, so fast automated diagnosis is necessary. In the field of …
Comparison of machine learning algorithms for classification of Big Data sets
This article analyzes and compares various Quantum machine learning algorithms on big
data. The main contribution of this article is to provide a new machine-learning approach …
data. The main contribution of this article is to provide a new machine-learning approach …
Fast Quantum Convolutional Neural Networks for Low-Complexity Object Detection in Autonomous Driving Applications
Object detection applications, especially in autonomous driving, have drawn attention due to
the advancements in deep learning. Additionally, with continuous improvements in classical …
the advancements in deep learning. Additionally, with continuous improvements in classical …
Quantum-inspired activation functions in the convolutional neural network
Driven by the significant advantages offered by quantum computing, research in quantum
machine learning has increased in recent years. While quantum speed-up has been …
machine learning has increased in recent years. While quantum speed-up has been …
Optimal Prognostic Accuracy: Machine Learning Approaches for COVID-19 Prognosis with Biomarkers and Demographic Information
The global emergence of the unprecedented COVID-19 pandemic in late 2019 has led to
millions of infections and thousands of fatalities, profoundly affecting various aspects of life …
millions of infections and thousands of fatalities, profoundly affecting various aspects of life …
A Hybrid Approach to Improve the Video Anomaly Detection Performance of Pixel-and Frame-Based Techniques Using Machine Learning Algorithms
With the rapid development in technology in recent years, the use of cameras and the
production of video and image data have similarly increased. Therefore, there is a great …
production of video and image data have similarly increased. Therefore, there is a great …
[PDF][PDF] Classification of Spine Images using Hybrid Quantum Neural Network Classifier
AA Hussein, AM Montaser, HA Elsayed - Quantum, 2024 - bit.kuas.edu.tw
This study classified images of the spine using three different models: the classical neural
network, the quantum neural network, and the hybrid quantum neural network with and …
network, the quantum neural network, and the hybrid quantum neural network with and …
[PDF][PDF] Hybrid Quantum Image Classification and Federated Learning for Hepatic Steatosis Diagnosis. Diagnostics 2024, 14, 558
L Lusnig, A Sagingalieva, M Surmach, T Protasevich… - 2024 - academia.edu
In the realm of liver transplantation, accurately determining hepatic steatosis levels is crucial.
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …
Recognizing the essential need for improved diagnostic precision, particularly for optimizing …