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 …
Automatic early diagnosis of Alzheimer's disease using 3D deep ensemble approach
Alzheimer's disease (AD) is considered the 6 leading cause of death worldwide. Early
diagnosis of AD is not an easy task, and no preventive cures have been discovered yet …
diagnosis of AD is not an easy task, and no preventive cures have been discovered yet …
[HTML][HTML] Systematic comparison of 3D Deep learning and classical machine learning explanations for Alzheimer's Disease detection
Black-box deep learning (DL) models trained for the early detection of Alzheimer's Disease
(AD) often lack systematic model interpretation. This work computes the activated brain …
(AD) often lack systematic model interpretation. This work computes the activated brain …
Attention based multi-task interpretable graph convolutional network for Alzheimer's disease analysis
S Jiang, Q Feng, H Li, Z Deng, Q Jiang - Pattern Recognition Letters, 2024 - Elsevier
Alzheimer's Disease impairs the memory and cognitive function of patients, and early
intervention can effectively mitigate its deterioration. Most existing methods for Alzheimer's …
intervention can effectively mitigate its deterioration. Most existing methods for Alzheimer's …
Interpretable and Accurate Identification of Job Seekers at Risk of Long-Term Unemployment: Explainable ML-Based Profiling
To tackle the societal and person-specific adverse consequences of long-term
unemployment, many public employment services (PES) have implemented data-driven …
unemployment, many public employment services (PES) have implemented data-driven …
A Siamese network optimization using genetic algorithm for brain diseases
The complex nature of human brain tissues is important in ensuring accurate diagnosis to
save human lives. Research on early detection of brain diseases has gained significant …
save human lives. Research on early detection of brain diseases has gained significant …
Deep interpretability methods for neuroimaging
MM Rahman - 2022 - scholarworks.gsu.edu
Brain dynamics are highly complex and yet hold the key to understanding brain function and
dysfunction. The dynamics captured by resting-state functional magnetic resonance imaging …
dysfunction. The dynamics captured by resting-state functional magnetic resonance imaging …
[HTML][HTML] MRI tractographic validation of drug-enhanced hepatic clearance of amyloid-beta and the therapeutic potential for Alzheimer's Disease: A pilot study
A Bhattacharjee, PK Roy - Brain Disorders, 2024 - Elsevier
Alzheimer's disease (AD) may require alternative therapeutic perspectives as current
interventions may sometimes be sub-optimal. Amyloid-beta 42 (Aβ 42) is mainly eliminated …
interventions may sometimes be sub-optimal. Amyloid-beta 42 (Aβ 42) is mainly eliminated …
Image Processing Using Morphology on Support Vector Machine Classification Model for Waste Image
Sorting waste has always been an important part of managing waste. The primary issue with
the waste sorting process has been the discomfort caused by prolonged contact with waste …
the waste sorting process has been the discomfort caused by prolonged contact with waste …
Sensitivity Analysis for Feature Importance in Predicting Alzheimer's Disease
Artificial Intelligence (AI) classifier models based on Deep Neural Networks (DNN) have
demonstrated superior performance in medical diagnostics. However, DNN models are …
demonstrated superior performance in medical diagnostics. However, DNN models are …