[HTML][HTML] Artificial intelligence models in the diagnosis of adult-onset dementia disorders: A review
G Battineni, N Chintalapudi, MA Hossain, G Losco… - Bioengineering, 2022 - mdpi.com
Background: The progressive aging of populations, primarily in the industrialized western
world, is accompanied by the increased incidence of several non-transmittable diseases …
world, is accompanied by the increased incidence of several non-transmittable diseases …
[Retracted] Facial Features Detection System To Identify Children With Autism Spectrum Disorder: Deep Learning Models
ZAT Ahmed, THH Aldhyani, ME Jadhav… - … Methods in Medicine, 2022 - Wiley Online Library
Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with brain
development that subsequently affects the physical appearance of the face. Autistic children …
development that subsequently affects the physical appearance of the face. Autistic children …
Multi-feature computational framework for combined signatures of dementia in underrepresented settings
Objective. The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD)
and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed …
and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed …
[HTML][HTML] Classification of Alzheimer's disease using MRI data based on Deep Learning Techniques
SE Sorour, AA Abd El-Mageed, KM Albarrak… - Journal of King Saud …, 2024 - Elsevier
Alzheimer's Disease (AD) is a worldwide concern impacting millions of people, with no
effective treatment known to date. Unlike cancer, which has seen improvement in preventing …
effective treatment known to date. Unlike cancer, which has seen improvement in preventing …
Deep Learning Based Model for Alzheimer's Disease Detection Using Brain MRI Images
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that causes problems
with memory, thinking, and behavior. And with time, symptoms become severe enough to …
with memory, thinking, and behavior. And with time, symptoms become severe enough to …
Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …
disorder among the elderly and is a leading cause of dementia. AD results in significant …
[HTML][HTML] Automatic Analysis of MRI Images for Early Prediction of Alzheimer's Disease Stages Based on Hybrid Features of CNN and Handcrafted Features
A Khalid, EM Senan, K Al-Wagih, MM Ali Al-Azzam… - Diagnostics, 2023 - mdpi.com
Alzheimer's disease (AD) is considered one of the challenges facing health care in the
modern century; until now, there has been no effective treatment to cure it, but there are …
modern century; until now, there has been no effective treatment to cure it, but there are …
[HTML][HTML] Alzheimer's disease detection from fused PET and MRI modalities using an ensemble classifier
Alzheimer's disease (AD) is an old-age disease that comes in different stages and directly
affects the different regions of the brain. The research into the detection of AD and its stages …
affects the different regions of the brain. The research into the detection of AD and its stages …
[HTML][HTML] Reinforcement-Learning-Based Localization of Hippocampus for Alzheimer's Disease Detection
Alzheimer's disease (AD) is a progressive neurodegenerative disorder primarily impacting
memory and cognitive functions. The hippocampus serves as a key biomarker associated …
memory and cognitive functions. The hippocampus serves as a key biomarker associated …
Role of Artificial Intelligence in Multinomial Decisions and Preventative Nutrition in Alzheimer's Disease
A Soares Dias Portela, V Saxena… - Molecular Nutrition & …, 2024 - Wiley Online Library
Alzheimer's disease (AD) affects 50 million people worldwide, an increase of 35 million
since 2015, and it is known for memory loss and cognitive decline. Considering the …
since 2015, and it is known for memory loss and cognitive decline. Considering the …