Leveraging 6G, extended reality, and IoT big data analytics for healthcare: A review

HF Ahmad, W Rafique, RU Rasool, A Alhumam… - Computer Science …, 2023 - Elsevier
In recent years, the healthcare industry has faced new challenges around staffing, human
interaction, and the adoption of telehealth. Technological innovations can improve …

Recent trends and advances in fundus image analysis: A review

S Iqbal, TM Khan, K Naveed, SS Naqvi… - Computers in Biology and …, 2022 - Elsevier
Automated retinal image analysis holds prime significance in the accurate diagnosis of
various critical eye diseases that include diabetic retinopathy (DR), age-related macular …

Comparative performance analysis of quantum machine learning with deep learning for diabetes prediction

H Gupta, H Varshney, TK Sharma, N Pachauri… - Complex & Intelligent …, 2022 - Springer
Background Diabetes, the fastest growing health emergency, has created several life-
threatening challenges to public health globally. It is a metabolic disorder and triggers many …

Multiclass seismic damage detection of buildings using quantum convolutional neural network

S Bhatta, J Dang - Computer‐Aided Civil and Infrastructure …, 2024 - Wiley Online Library
The traditional visual inspection technique for damage assessment of buildings immediately
after an earthquake can be time‐consuming, labor‐intensive, and risky. Numerous studies …

[PDF][PDF] Applications of quantum computing in telecom e-commerce: Analysis of qkd, qaoa, and qml for data encryption, speed optimization, and ai-driven customer …

R Khurana - Quarterly Journal of Emerging Technologies and …, 2022 - researchgate.net
Quantum computing methods take advantage of the principles of superposition and
entanglement to facilitate parallel computing that is beyond the reach of classical systems …

Contemporary quantum computing use cases: taxonomy, review and challenges

J Singh, KS Bhangu - Archives of Computational Methods in Engineering, 2023 - Springer
Recently, the popularity of using the expressive power of quantum computing to solve
known, challenging problems has increased remarkably. This study aims to develop a clear …

Semiconductor defect detection by hybrid classical-quantum deep learning

YF Yang, M Sun - … of the IEEE/CVF Conference on …, 2022 - openaccess.thecvf.com
With the rapid development of artificial intelligence and autonomous driving technology, the
demand for semiconductors is projected to rise substantially. However, the massive …

Quantum-inspired machine learning for 6G: fundamentals, security, resource allocations, challenges, and future research directions

TQ Duong, JA Ansere, B Narottama… - IEEE Open Journal …, 2022 - ieeexplore.ieee.org
Quantum computing is envisaged as an evolving paradigm for solving computationally
complex optimization problems with a large-number factorization and exhaustive search …

Quantum machine learning revolution in healthcare: a systematic review of emerging perspectives and applications

U Ullah, B Garcia-Zapirain - IEEE Access, 2024 - ieeexplore.ieee.org
Quantum computing (QC) stands apart from traditional computing systems by employing
revolutionary techniques for processing information. It leverages the power of quantum bits …

Urban quantum leap: A comprehensive review and analysis of quantum technologies for smart cities

AB Bonab, M Fedele, V Formisano, I Rudko - Cities, 2023 - Elsevier
Contemporary smart city solutions rely on standardized von Neumann architecture, in which
single data units are coded as “0” or “1.” Conversely, urban quantum technologies rely on …