Prediction and classification of Alzheimer's disease using machine learning techniques in 3D MR images

KN Rao, BR Gandhi, MV Rao, S Javvadi… - … and Smart Systems …, 2023 - ieeexplore.ieee.org
Memory and thought-related brain cells are damaged permanently by Alzheimer's disease. It
has a fatal outcome since it causes death. As a result, early detection of Alzheimer's disease …

Intelligent decision support systems for dementia care: A scoping review

AE Andargoli, N Ulapane, TA Nguyen… - Artificial Intelligence in …, 2024 - Elsevier
In the context of dementia care, Artificial Intelligence (AI) powered clinical decision support
systems have the potential to enhance diagnosis and management. However, the scope …

Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights

AS Tang, KP Rankin, G Cerono, S Miramontes, H Mills… - Nature Aging, 2024 - nature.com
Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before
irreversible disease progression. We demonstrate that electronic health records from the …

[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 …

Early Detection of Alzheimer's Disease: An Extensive Review of Advancements in Machine Learning Mechanisms Using an Ensemble and Deep Learning Technique

RP Neelakandan, R Kandasamy, B Subbiyan… - Engineering …, 2023 - mdpi.com
Alzheimer's disease (AD) is the most common form of dementia in senior individuals. It is a
progressive neurological ailment that predominantly affects memory, cognition, and …

[HTML][HTML] The microRNA-485-3p concentration in salivary exosome-enriched extracellular vesicles is related to amyloid β deposition in the brain of patients with …

IS Ryu, DH Kim, JY Ro, BG Park, SH Kim, JY Im… - Clinical …, 2023 - Elsevier
Objectives Alzheimer's disease (AD) is an irreversible neurodegenerative disease
characterized by progressive long-term memory loss and cognitive dysfunction …

Pipelined deep learning architecture for the detection of Alzheimer's disease

T Prasath, V Sumathi - Biomedical Signal Processing and Control, 2024 - Elsevier
The progressive neurodegenerative disease in the human brain causes Alzheimer's disease
(AD). The earlier detection helps to slowdown the progression of AD using continuous …

A new approach for multimodal usage of gene expression and its image representation for the detection of Alzheimer's disease

UM Akkaya, H Kalkan - Biomolecules, 2023 - mdpi.com
Alzheimer's disease (AD) is a complex neurodegenerative disorder and the multifaceted
nature of it requires innovative approaches that integrate various data modalities to enhance …

Governing fiduciary relationships or building up a governance model for trust in AI? Review of healthcare as a socio-technical system

MB Unver - International Review of Law, Computers & Technology, 2023 - Taylor & Francis
Fiduciary law aims to mitigate the inherent risk of 'trust', which helps restore interpersonal
trust. It remains to be answered how trust should be governed in an AI-driven socio-technical …

Comprehensive overview of Alzheimer's disease utilizing Machine Learning approaches

R Kumar, C Azad - Multimedia Tools and Applications, 2024 - Springer
Alzheimer's disease is a common and complex brain disorder that primarily affects the
elderly. Because it is progressing and has few effective therapies, it requires a thorough …