Machine learning methods for predicting progression from mild cognitive impairment to Alzheimer's disease dementia: a systematic review

S Grueso, R Viejo-Sobera - Alzheimer's research & therapy, 2021 - Springer
Background An increase in lifespan in our society is a double-edged sword that entails a
growing number of patients with neurocognitive disorders, Alzheimer's disease being the …

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

G Lombardi, G Crescioli, E Cavedo… - Cochrane Database …, 2020 - cochranelibrary.com
Background Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic
predementia phase of Alzheimer's disease dementia, characterised by cognitive and …

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI …

SI Dimitriadis, D Liparas, MN Tsolaki… - Journal of neuroscience …, 2018 - Elsevier
Background In the era of computer-assisted diagnostic tools for various brain diseases,
Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the …

MRI asymmetry index of hippocampal subfields increases through the continuum from the mild cognitive impairment to the Alzheimer's disease

A Sarica, R Vasta, F Novellino, MG Vaccaro… - Frontiers in …, 2018 - frontiersin.org
Objective: It is well-known that the hippocampus presents significant asymmetry in
Alzheimer's disease (AD) and that difference in volumes between left and right exists and …

Wavelet entropy and directed acyclic graph support vector machine for detection of patients with unilateral hearing loss in MRI scanning

S Wang, M Yang, S Du, J Yang, B Liu… - Frontiers in …, 2016 - frontiersin.org
Highlights We develop computer-aided diagnosis system for unilateral hearing loss
detection in structural magnetic resonance imaging. Wavelet entropy is introduced to extract …

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares

J Ramírez, JM Górriz, A Ortiz… - Journal of neuroscience …, 2018 - Elsevier
Background Alzheimer's disease (AD) is the most common cause of dementia in the elderly
and affects approximately 30 million individuals worldwide. Mild cognitive impairment (MCI) …

Explainable boosting machine for predicting Alzheimer's disease from MRI hippocampal subfields

A Sarica, A Quattrone, A Quattrone - International Conference on Brain …, 2021 - Springer
Although automatic prediction of Alzheimer's disease (AD) from Magnetic Resonance
Imaging (MRI) showed excellent performance, Machine Learning (ML) algorithms often …

The Healthy Brain Initiative (HBI): A prospective cohort study protocol

LM Besser, S Chrisphonte, MJ Kleiman, D O'Shea… - Plos one, 2023 - journals.plos.org
Background The Health Brain Initiative (HBI), established by University of Miami's
Comprehensive Center for Brain Health (CCBH), follows racially/ethnically diverse older …

An ensemble learning system for a 4-way classification of Alzheimer's disease and mild cognitive impairment

D Yao, VD Calhoun, Z Fu, Y Du, J Sui - Journal of neuroscience methods, 2018 - Elsevier
Discriminating Alzheimer's disease (AD) from its prodromal form, mild cognitive impairment
(MCI), is a significant clinical problem that may facilitate early diagnosis and intervention, in …

Atrophy of hippocampal subfields and amygdala nuclei in subjects with mild cognitive impairment progressing to Alzheimer's disease

M Punzi, C Sestieri, E Picerni, AM Chiarelli, C Padulo… - Heliyon, 2024 - cell.com
The hippocampus and amygdala are the first brain regions to show early signs of
Alzheimer's Disease (AD) pathology. AD is preceded by a prodromal stage known as Mild …