QUANT-PHLGDec 3, 2024

A Study on Quantum Neural Networks in Healthcare 5.0

arXiv:2412.06818v15 citationsh-index: 1
Originality Synthesis-oriented
AI Analysis

It addresses the transition to collaborative healthcare systems using quantum technologies, but is incremental as it primarily reviews and synthesizes existing literature.

This study reviews the integration of quantum neural networks in healthcare analytics under Healthcare 5.0, identifying research gaps and potential challenges without presenting new experimental results or concrete performance metrics.

The working environment in healthcare analytics is transforming with the emergence of healthcare 5.0 and the advancements in quantum neural networks. In addition to analyzing a comprehensive set of case studies, we also review relevant literature from the fields of quantum computing applications and smart healthcare analytics, focusing on the implications of quantum deep neural networks. This study aims to shed light on the existing research gaps regarding the implications of quantum neural networks in healthcare analytics. We argue that the healthcare industry is currently transitioning from automation towards genuine collaboration with quantum networks, which presents new avenues for research and exploration. Specifically, this study focuses on evaluating the performance of Healthcare 5.0, which involves the integration of diverse quantum machine learning and quantum neural network systems. This study also explores a range of potential challenges and future directions for Healthcare 5.0, particularly focusing on the integration of quantum neural networks.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes