[HTML][HTML] Medical image registration in the era of Transformers: a recent review
Motivated by the rapid and current progress to develop intelligent image-guided intervention
tools, we aim in this paper to present, a recent review of a specific family of deep learning …
tools, we aim in this paper to present, a recent review of a specific family of deep learning …
[HTML][HTML] Optimized ensemble learning approach with explainable AI for improved heart disease prediction
Recent advances in machine learning (ML) have shown great promise in detecting heart
disease. However, to ensure the clinical adoption of ML models, they must not only be …
disease. However, to ensure the clinical adoption of ML models, they must not only be …
Brain tumor detection and classification in MRI using hybrid ViT and GRU model with explainable AI in Southern Bangladesh
Brain tumor, a leading cause of uncontrolled cell growth in the central nervous system,
presents substantial challenges in medical diagnosis and treatment. Early and accurate …
presents substantial challenges in medical diagnosis and treatment. Early and accurate …
Unlocking the potential of XAI for improved alzheimer's disease detection and classification using a ViT-GRU model
Alzheimer's Disease (AD) is a significant cause of dementia worldwide, and its progression
from mild to severe affects an individual's ability to perform daily activities independently …
from mild to severe affects an individual's ability to perform daily activities independently …
An Enhanced Technique of COVID‐19 Detection and Classification Using Deep Convolutional Neural Network from Chest X‐Ray and CT Images
Background. Coronavirus disease (COVID‐19) is an infectious illness that spreads widely
over a short period of time and finally causes a pandemic. Unfortunately, the lack of …
over a short period of time and finally causes a pandemic. Unfortunately, the lack of …
Enhancing lung abnormalities diagnosis using hybrid DCNN-ViT-GRU model with explainable AI: A deep learning approach
In this study, we propose a novel approach called DCNN-ViT-GRU, which combines deep
Convolutional Neural Networks (CNNs) with Gated Recurrent Units (GRUs) and the Vision …
Convolutional Neural Networks (CNNs) with Gated Recurrent Units (GRUs) and the Vision …
A visual data unsupervised disentangled representation learning framework: Contrast disentanglement based on variational auto-encoder
C Huang, J Cai, S Luo, S Wang, G Yang, H Lei… - … Applications of Artificial …, 2025 - Elsevier
To discover and learn interpretable factors behind the visual data, many approaches use
extra regularization terms in learning disentangled representations, which lead to poor …
extra regularization terms in learning disentangled representations, which lead to poor …
Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors
S Campanioni, C Veiga, JM Prieto-González… - Plos one, 2024 - journals.plos.org
Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges
in timely diagnosis and personalized patient management. The application of Artificial …
in timely diagnosis and personalized patient management. The application of Artificial …
A novel hybrid ViT-LSTM model with explainable AI for brain stroke detection and classification in CT images: A case study of Rajshahi region
Computed tomography (CT) scans play a key role in the diagnosis of stroke, a leading cause
of morbidity and mortality worldwide. However, interpreting these scans is often challenging …
of morbidity and mortality worldwide. However, interpreting these scans is often challenging …
Heart disease detection using ensemble machine learning technique based on various risk factors
VS Chithra, HS Shashank… - 2024 Second International …, 2024 - ieeexplore.ieee.org
CVD remains one of the significant current global health burdens, with the need for
sophisticated approaches to predict it accurately and in good time. This paper articulates a …
sophisticated approaches to predict it accurately and in good time. This paper articulates a …