Deep learning for Alzheimer's disease diagnosis: A survey
M Khojaste-Sarakhsi, SS Haghighi… - Artificial intelligence in …, 2022 - Elsevier
Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
Early diagnosis of Alzheimer's disease based on deep learning: A systematic review
Background The improvement of health indicators and life expectancy, especially in
developed countries, has led to population growth and increased age-related diseases …
developed countries, has led to population growth and increased age-related diseases …
Preventing dataset shift from breaking machine-learning biomarkers
Abstract Machine learning brings the hope of finding new biomarkers extracted from cohorts
with rich biomedical measurements. A good biomarker is one that gives reliable detection of …
with rich biomedical measurements. A good biomarker is one that gives reliable detection of …
Regional radiomics similarity networks reveal distinct subtypes and abnormality patterns in mild cognitive impairment
Individuals with mild cognitive impairment (MCI) of different subtypes show distinct
alterations in network patterns. The first aim of this study is to identify the subtypes of MCI by …
alterations in network patterns. The first aim of this study is to identify the subtypes of MCI by …
Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review
BM de Vries, GJC Zwezerijnen, GL Burchell… - Frontiers in …, 2023 - frontiersin.org
Rational Deep learning (DL) has demonstrated a remarkable performance in diagnostic
imaging for various diseases and modalities and therefore has a high potential to be used …
imaging for various diseases and modalities and therefore has a high potential to be used …
An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data
Functional magnetic resonance imaging (fMRI) as a promising tool to investigate psychotic
disorders can be decomposed into useful imaging features such as time courses (TCs) of …
disorders can be decomposed into useful imaging features such as time courses (TCs) of …
Basic of machine learning and deep learning in imaging for medical physicists
L Manco, N Maffei, S Strolin, S Vichi, L Bottazzi… - Physica Medica, 2021 - Elsevier
The manuscript aims at providing an overview of the published algorithms/automation tool
for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed …
for artificial intelligence applied to imaging for Healthcare. A PubMed search was performed …
Alzheimer's disease diagnosis with brain structural mri using multiview-slice attention and 3D convolution neural network
Numerous artificial intelligence (AI) based approaches have been proposed for automatic
Alzheimer's disease (AD) prediction with brain structural magnetic resonance imaging …
Alzheimer's disease (AD) prediction with brain structural magnetic resonance imaging …
Interpretable machine learning for dementia: a systematic review
Introduction Machine learning research into automated dementia diagnosis is becoming
increasingly popular but so far has had limited clinical impact. A key challenge is building …
increasingly popular but so far has had limited clinical impact. A key challenge is building …
A novel explainable neural network for Alzheimer's disease diagnosis
Visual classification for medical images has been dominated by convolutional neural
networks (CNNs) for years. Though they have shown great performance on accuracy, some …
networks (CNNs) for years. Though they have shown great performance on accuracy, some …