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 …

Review of medical image processing using quantum-enabled algorithms

F Yan, H Huang, W Pedrycz, K Hirota - Artificial Intelligence Review, 2024 - Springer
Efficient and reliable storage, analysis, and transmission of medical images are imperative
for accurate diagnosis, treatment, and management of various diseases. Since quantum …

Analysis of quantum machine learning algorithms in noisy channels for classification tasks in the iot extreme environment

SK Satpathy, V Vibhu, BK Behera… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
By 2050, there will be a 50% rise in energy demand, and existing natural and renewable
resources will be under extreme scrutiny. Optimizing current power generation and …

Efficient superpixel-based brain MRI segmentation using multi-scale morphological gradient reconstruction and quantum clustering

AG Oskouei, N Abdolmaleki, A Bouyer… - … Signal Processing and …, 2025 - Elsevier
Segmentation of brain MRI images is a fundamental task in medical image analysis.
However, existing clustering methods often face significant challenges, including high …

Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review

A Ghasemi, S Hashtarkhani, DL Schwartz… - Cancer …, 2024 - Wiley Online Library
With the advances in artificial intelligence (AI), data‐driven algorithms are becoming
increasingly popular in the medical domain. However, due to the nonlinear and complex …

Variational quantum and quantum-inspired clustering

P Bermejo, R Orús - Scientific Reports, 2023 - nature.com
Here we present a quantum algorithm for clustering data based on a variational quantum
circuit. The algorithm allows to classify data into many clusters, and can easily be …

Anatomical prior-based vertebral landmark detection for spinal disorder diagnosis

Y Yang, Y Wang, T Liu, M Wang, M Sun, S Song… - Artificial Intelligence in …, 2025 - Elsevier
As one of fundamental ways to interpret spine images, detection of vertebral landmarks is an
informative prerequisite for further diagnosis and management of spine disorders such as …

[HTML][HTML] Local interpretable model-agnostic explanation approach for medical imaging analysis: A systematic literature review

SU Hassan, SJ Abdulkadir, MSM Zahid… - Computers in Biology …, 2025 - Elsevier
Background: The interpretability and explainability of machine learning (ML) and artificial
intelligence systems are critical for generating trust in their outcomes in fields such as …

Expert-level diagnosis of pediatric posterior fossa tumors via consistency calibration

C Sun, Z Yan, Y Zhang, X Tian, J Gong - Knowledge-Based Systems, 2024 - Elsevier
Accurate diagnosis of pediatric posterior fossa tumors (PFTs) is critical for saving lives;
however, the limited number of specialists makes accurate diagnostics scarce. To make the …

[HTML][HTML] A Comprehensive Review of Explainable AI for Disease Diagnosis

AA Biswas - Array, 2024 - Elsevier
Nowadays, artificial intelligence (AI) has been utilized in several domains of the healthcare
sector. Despite its effectiveness in healthcare settings, its massive adoption remains limited …