Explainable artificial intelligence in Alzheimer's disease classification: A systematic review
The unprecedented growth of computational capabilities in recent years has allowed
Artificial Intelligence (AI) models to be developed for medical applications with remarkable …
Artificial Intelligence (AI) models to be developed for medical applications with remarkable …
Interpreting artificial intelligence models: a systematic review on the application of LIME and SHAP in Alzheimer's disease detection
Explainable artificial intelligence (XAI) has gained much interest in recent years for its ability
to explain the complex decision-making process of machine learning (ML) and deep …
to explain the complex decision-making process of machine learning (ML) and deep …
Exploring deep transfer learning ensemble for improved diagnosis and classification of alzheimer's disease
Alzheimer's disease (AD) is a progressive and irreversible neurological disorder that affects
millions of people worldwide. Early detection and accurate diagnosis of AD are crucial for …
millions of people worldwide. Early detection and accurate diagnosis of AD are crucial for …
Early detection of Alzheimer's disease from cortical and hippocampal local field potentials using an ensembled machine learning model
Early diagnosis of Alzheimer's disease (AD) is a very challenging problem and has been
attempted through data-driven methods in recent years. However, considering the inherent …
attempted through data-driven methods in recent years. However, considering the inherent …
[PDF][PDF] Performance evaluation of deep, shallow and ensemble machine learning methods for the automated classification of Alzheimer's disease
Artificial Intelligence (AI)-based approaches are crucial in Computer-Aided Diagnosis (CAD)
for various medical applications. Their ability to quickly and accurately learn from complex …
for various medical applications. Their ability to quickly and accurately learn from complex …
Application of explainable artificial intelligence in alzheimer's disease classification: A systematic review
Abstract Context: Artificial Intelligence (AI) in the medical domain has achieved remarkable
results on various metrics primarily due to recent advancements in computational …
results on various metrics primarily due to recent advancements in computational …
Bagging the best: a hybrid SVM-KNN ensemble for accurate and early detection of Alzheimer's and Parkinson's diseases
Deep Learning (DL) techniques have shown promise in the early detection of
neurodegenerative diseases due to their ability to analyze large amounts of medical data …
neurodegenerative diseases due to their ability to analyze large amounts of medical data …
Multi-Planar MRI-Based Classification of Alzheimer's Disease Using Tree-Based Machine Learning Algorithms
While most contemporary algorithms typically utilize MRI data from a single plane, this study
highlights the importance of incorporating multiplanar MRI features for enhanced …
highlights the importance of incorporating multiplanar MRI features for enhanced …
Deep Learning for Alzheimer's Disease Prediction: A Comprehensive Review
Alzheimer's disease (AD) is a neurological disorder that significantly impairs cognitive
function, leading to memory loss and eventually death. AD progresses through three stages …
function, leading to memory loss and eventually death. AD progresses through three stages …
VisTAD: A Vision Transformer Pipeline for the Classification of Alzheimer's Disease
In recent times, the Visual Transformer (VT) has emerged as a powerful alternative to the
conventional Convolutional Neural Networks (CNNs) for their superior attention mechanism …
conventional Convolutional Neural Networks (CNNs) for their superior attention mechanism …