Early detection of dementia using artificial intelligence and multimodal features with a focus on neuroimaging: A systematic literature review
O Grigas, R Maskeliunas, R Damaševičius - Health and Technology, 2024 - Springer
Purpose This paper is a systematic literature review of the use of artificial intelligence
techniques to detect early dementia. It focuses on multi-modal feature analysis in …
techniques to detect early dementia. It focuses on multi-modal feature analysis in …
[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 …
A Multimodal Approach Integrating Convolutional and Recurrent Neural Networks for Alzheimer's Disease Temporal Progression Prediction
DS Hl, SM Thomas - … of the IEEE/CVF Conference on …, 2024 - openaccess.thecvf.com
Alzheimer's Disease (AD) poses a substantial healthcare challenge marked by cognitive
decline and a lack of definitive treatments. As the global population ages the prevalence of …
decline and a lack of definitive treatments. As the global population ages the prevalence of …
Assessing the Reliability of Machine Learning Models Applied to the Mental Health Domain Using Explainable AI
V Pendyala, H Kim - Electronics, 2024 - mdpi.com
Machine learning is increasingly and ubiquitously being used in the medical domain.
Evaluation metrics like accuracy, precision, and recall may indicate the performance of the …
Evaluation metrics like accuracy, precision, and recall may indicate the performance of the …
Understanding the role of self-attention in a Transformer model for the discrimination of SCD from MCI using resting-state EEG
The identification of EEG biomarkers to discriminate Subjective Cognitive Decline (SCD)
from Mild Cognitive Impairment (MCI) conditions is a complex task which requires great …
from Mild Cognitive Impairment (MCI) conditions is a complex task which requires great …
A Comparative Analysis of LIME and SHAP Interpreters with Explainable ML-Based Diabetes Predictions
Explainable artificial intelligence is beneficial in converting opaque machine learning
models into transparent ones and outlining how each one makes decisions in the healthcare …
models into transparent ones and outlining how each one makes decisions in the healthcare …
An eXplainable Artificial Intelligence Methodology on Big Data Architecture
Although artificial intelligence has become part of everyone's real life, a trust crisis against
such systems is occurring, thus increasing the need to explain black-box predictions …
such systems is occurring, thus increasing the need to explain black-box predictions …
Intelligent explainable optical sensing on Internet of nanorobots for disease detection
N Mesgaribarzi, Y Djenouri, AN Belbachir… - Nanotechnology …, 2024 - degruyter.com
Combining deep learning (DL) with nanotechnology holds promise for transforming key
facets of nanoscience and technology. This synergy could pave the way for groundbreaking …
facets of nanoscience and technology. This synergy could pave the way for groundbreaking …
ML-Powered Handwriting Analysis for Early Detection of Alzheimer's Disease
Alzheimer's disease (AD) is a progressive, incurable condition leading to decline of nerve
cells and cognitive functions over time. Early detection is essential for improving quality of …
cells and cognitive functions over time. Early detection is essential for improving quality of …
AXIAL: Attention-based eXplainability for Interpretable Alzheimer's Localized Diagnosis using 2D CNNs on 3D MRI brain scans
This study presents an innovative method for Alzheimer's disease diagnosis using 3D MRI
designed to enhance the explainability of model decisions. Our approach adopts a soft …
designed to enhance the explainability of model decisions. Our approach adopts a soft …