Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

P Moridian, N Ghassemi, M Jafari… - Frontiers in Molecular …, 2022 - frontiersin.org
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …

Functional magnetic resonance imaging, deep learning, and Alzheimer's disease: A systematic review

SL Warren, AA Moustafa - Journal of Neuroimaging, 2023 - Wiley Online Library
Alzheimer's disease (AD) is currently diagnosed using a mixture of psychological tests and
clinical observations. However, these diagnoses are not perfect, and additional diagnostic …

Early diagnosis of brain tumour mri images using hybrid techniques between deep and machine learning

EM Senan, ME Jadhav, TH Rassem… - … Methods in Medicine, 2022 - Wiley Online Library
Cancer is considered one of the most aggressive and destructive diseases that shortens the
average lives of patients. Misdiagnosed brain tumours lead to false medical intervention …

Eye tracking-based diagnosis and early detection of autism spectrum disorder using machine learning and deep learning techniques

IA Ahmed, EM Senan, TH Rassem, MAH Ali… - Electronics, 2022 - mdpi.com
Eye tracking is a useful technique for detecting autism spectrum disorder (ASD). One of the
most important aspects of good learning is the ability to have atypical visual attention. The …

Multi-method analysis of medical records and MRI images for early diagnosis of dementia and Alzheimer's disease based on deep learning and hybrid methods

BA Mohammed, EM Senan, TH Rassem, NM Makbol… - Electronics, 2021 - mdpi.com
Dementia and Alzheimer's disease are caused by neurodegeneration and poor
communication between neurons in the brain. So far, no effective medications have been …

A review of deep transfer learning approaches for class-wise prediction of Alzheimer's disease using MRI images

PS Sisodia, GK Ameta, Y Kumar, N Chaplot - Archives of Computational …, 2023 - Springer
Alzheimer's disease is an irreversible, progressive neurodegenerative disorder that destroys
the brain and memory functionalities. In Alzheimer's disease, the brain starts shrinking, and …

A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer's disease, and mild cognitive impairment using brain 18F-FDG PET

K Etminani, A Soliman, A Davidsson, JR Chang… - European journal of …, 2022 - Springer
Purpose The purpose of this study is to develop and validate a 3D deep learning model that
predicts the final clinical diagnosis of Alzheimer's disease (AD), dementia with Lewy bodies …

Diagnosis and detection of Alzheimer's disease using learning algorithm

GP Shukla, S Kumar, SK Pandey… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
In Computer-Aided Detection (CAD) brain disease classification is a vital issue. Alzheimer's
Disease (AD) and brain tumors are the primary reasons of death. The studies of these …

A smart Alzheimer's patient monitoring system with IoT-assisted technology through enhanced deep learning approach

R Arunachalam, G Sunitha, SK Shukla… - … and Information Systems, 2023 - Springer
Earlier detection of Alzheimer's disease is more significant for improving the quality of the
patient's life. This aspect may reduce the fatality rate among the population and also …

An improved deep residual network prediction model for the early diagnosis of Alzheimer's disease

H Sun, A Wang, W Wang, C Liu - Sensors, 2021 - mdpi.com
The early diagnosis of Alzheimer's disease (AD) can allow patients to take preventive
measures before irreversible brain damage occurs. It can be seen from cross-sectional …