Applications of deep learning in Alzheimer's disease: A systematic literature review of current trends, methodologies, challenges, innovations, and future directions
S Toumaj, A Heidari, R Shahhosseini… - Artificial Intelligence …, 2024 - Springer
Alzheimer's Disease (AD) constitutes a significant global health issue. In the next 40 years, it
is expected to affect 106 million people. Although more and more people are getting AD …
is expected to affect 106 million people. Although more and more people are getting AD …
Alzheimer's Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …
approaches. This systematic review surveys the recent literature (2018 onwards) to …
An unsupervised learning approach to diagnosing Alzheimer's disease using brain magnetic resonance imaging scans
Y Liu, S Mazumdar, PA Bath… - International Journal of …, 2023 - Elsevier
Background Alzheimer's disease (AD) is the most common cause of dementia, characterised
by behavioural and cognitive impairment. Due to the lack of effectiveness of manual …
by behavioural and cognitive impairment. Due to the lack of effectiveness of manual …
Advanced brain imaging for the diagnosis of Alzheimer disease
Brain imaging techniques using PET improve our understanding of the different AD-related
pathologies and their relationship with each other along the course of disease. With more …
pathologies and their relationship with each other along the course of disease. With more …
An explainable machine learning approach for Alzheimer's disease classification
The early diagnosis of Alzheimer's disease (AD) presents a significant challenge due to the
subtle biomarker changes often overlooked. Machine learning (ML) models offer a …
subtle biomarker changes often overlooked. Machine learning (ML) models offer a …
A review of artificial intelligence methods for Alzheimer's disease diagnosis: Insights from neuroimaging to sensor data analysis
Alzheimer's disease is the most common cause of dementia, gradually impairing memory,
intellectual, learning, and organizational capacities. An individual's capacity to perform …
intellectual, learning, and organizational capacities. An individual's capacity to perform …
Potential Ocular Biomarkers for Early Detection of Alzheimer's Disease and Their Roles in Artificial Intelligence Studies
P Chaitanuwong, P Singhanetr, M Chainakul… - Neurology and …, 2023 - Springer
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is
believed to be essential to disease management because it enables physicians to initiate …
believed to be essential to disease management because it enables physicians to initiate …
Deep learning-based, fully automated, pediatric brain segmentation
MJ Kim, EP Hong, MS Yum, YJ Lee, J Kim, TS Ko - Scientific Reports, 2024 - nature.com
The purpose of this study was to demonstrate the performance of a fully automated, deep
learning-based brain segmentation (DLS) method in healthy controls and in patients with …
learning-based brain segmentation (DLS) method in healthy controls and in patients with …
[HTML][HTML] 人工智能在阿尔茨海默病临床诊疗中的研究热点及前沿趋势分析
余如霞， 姜婧， 王湫澄， 王越， 赵小月 - 中国全科医学, 2024 - chinagp.net
背景目前, 人工智能应用于阿尔茨海默病(AD) 领域的研究论文数量增幅较大,
明确该领域最新研究热点和未来发展趋势十分重要. 目的通过应用文献计量学分析 …
明确该领域最新研究热点和未来发展趋势十分重要. 目的通过应用文献计量学分析 …
Automated neuroradiological support systems for multiple cerebrovascular disease markers--A systematic review and meta-analysis
Cerebrovascular diseases (CVD) can lead to stroke and dementia. Stroke is the second
leading cause of death world wide and dementia incidence is increasing by the year. There …
leading cause of death world wide and dementia incidence is increasing by the year. There …