A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

S Rathore, M Habes, MA Iftikhar, A Shacklett… - NeuroImage, 2017 - Elsevier
Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …

The heterogeneity problem: approaches to identify psychiatric subtypes

E Feczko, O Miranda-Dominguez, M Marr… - Trends in cognitive …, 2019 - cell.com
The imprecise nature of psychiatric nosology restricts progress towards characterizing and
treating mental health disorders. One issue is the 'heterogeneity problem': different causal …

Joint classification and regression via deep multi-task multi-channel learning for Alzheimer's disease diagnosis

M Liu, J Zhang, E Adeli, D Shen - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain
diseases and predicting clinical scores using magnetic resonance imaging (MRI) have …

Alzheimer's disease diagnostics by a deeply supervised adaptable 3D convolutional network

E Hosseini-Asl, G Gimel'farb, A El-Baz - arxiv preprint arxiv:1607.00556, 2016 - arxiv.org
Early diagnosis, playing an important role in preventing progress and treating the
Alzheimer's disease (AD), is based on classification of features extracted from brain images …

Alzheimer's disease diagnostics by adaptation of 3D convolutional network

E Hosseini-Asl, R Keynton… - 2016 IEEE international …, 2016 - ieeexplore.ieee.org
Early diagnosis, playing an important role in preventing progress and treating the
Alzheimer's disease (AD), is based on classification of features extracted from brain images …

Computational psychiatry as a bridge from neuroscience to clinical applications

QJM Huys, TV Maia, MJ Frank - Nature neuroscience, 2016 - nature.com
Translating advances in neuroscience into benefits for patients with mental illness presents
enormous challenges because it involves both the most complex organ, the brain, and its …

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge

EE Bron, M Smits, WM Van Der Flier, H Vrenken… - NeuroImage, 2015 - Elsevier
Algorithms for computer-aided diagnosis of dementia based on structural MRI have
demonstrated high performance in the literature, but are difficult to compare as different data …

[HTML][HTML] From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics

T Wolfers, JK Buitelaar, CF Beckmann, B Franke… - Neuroscience & …, 2015 - Elsevier
Psychiatric disorders are increasingly being recognised as having a biological basis, but
their diagnosis is made exclusively behaviourally. A promising approach for …

[HTML][HTML] Comparison of individualized behavioral predictions across anatomical, diffusion and functional connectivity MRI

LQR Ooi, J Chen, S Zhang, R Kong, A Tam, J Li… - NeuroImage, 2022 - Elsevier
A fundamental goal across the neurosciences is the characterization of relationships linking
brain anatomy, functioning, and behavior. Although various MRI modalities have been …

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

J Samper-González, N Burgos, S Bottani, S Fontanella… - NeuroImage, 2018 - Elsevier
A large number of papers have introduced novel machine learning and feature extraction
methods for automatic classification of Alzheimer's disease (AD). However, while the vast …