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 …
[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
ID Mienye, N Jere - Information, 2024 - mdpi.com
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 …
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 …
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 …
Hybrid CNN-LSTM Transfer Learning for Dengue Diagnosis from Raman Spectroscopy Images
The diagnosis of dengue fever can be made quickly and effectively with Raman
spectroscopy. However, the diagnostic procedure presents difficulties; for example, the …
spectroscopy. However, the diagnostic procedure presents difficulties; for example, the …
Integrating Explainable AI: Breakthroughs in Medical Diagnosis and Surgery
A Henriques, H Parola, R Gonçalves… - World Conference on …, 2024 - Springer
The challenge of explaining the results generated by artificial intelligence (AI) is a significant
obstacle to their widespread acceptance, which is why increased attention has been paid to …
obstacle to their widespread acceptance, which is why increased attention has been paid to …
Original Research Article Histopathological parameter and brain tumor mapping using distributed optimizer tuned explainable AI classifier
Brain tumors represent a critical and severe challenge worldwide early and accurate
diagnosis is necessary to increase the predictions for individuals with brain tumors. Several …
diagnosis is necessary to increase the predictions for individuals with brain tumors. Several …
Empowering cardiovascular disease diagnosis with machine and deep learning approaches
M Sáez Carazo - 2024 - diva-portal.org
Cardiovascular diseases are the leading cause of death worldwide, and their diagnosis can
be a complex process which involves several tests and medical procedures. The addition of …
be a complex process which involves several tests and medical procedures. The addition of …