Deep Learning-Based Multilevel Classification of Alzheimer’s Disease Using Non-invasive Functional Near-Infrared Spectroscopy

Thi Kieu Khanh Ho(Mila - Quebec Artificial Intelligence Institute), Jeonghwan Gwak(Korea National University of Transportation), Byeong C. Kim(Chonnam National University Hospital), Kun Ho Lee(Chosun University), Jae Gwan Kim(Gwangju Institute of Science and Technology), Jong‐In Song(Gwangju Institute of Science and Technology), Minhee Kim(Gwangju Institute of Science and Technology), Younghun Jeon(Gwangju Institute of Science and Technology)
Frontiers in Aging Neuroscience
April 26, 2022
10.3389/fnagi.2022.810125
Cited by 37

Related Papers

Regional analysis of FDG and PIB-PET images in normal aging, mild cognitive impairment, and Alzheimer’s disease
|European Journal of Nuclear Medicine and Molecular Imaging|2008|277
Endovascular Treatment and the Outcomes of Atherosclerotic Intracranial Stenosis in Patients With Hyperacute Stroke
|Neurosurgery|2015|179
Ensembles of Patch-Based Classifiers for Diagnosis of Alzheimer Diseases
|IEEE Access|2019|150
Volumetric Feature-Based Alzheimer’s Disease Diagnosis From sMRI Data Using a Convolutional Neural Network and a Deep Neural Network
|IEEE Access|2021|118
Acute stress causes rapid synaptic insertion of Ca2+-permeable AMPA receptors to facilitate long-term potentiation in the hippocampus
|Brain|2013|110