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 …
Handwriting changes in Alzheimer's disease: A systematic review
CP Fernandes, G Montalvo… - Journal of …, 2023 - journals.sagepub.com
Background: Handwriting is a complex process involving fine motor skills, kinesthetic
components, and several cognitive domains, often impaired by Alzheimer's disease (AD) …
components, and several cognitive domains, often impaired by Alzheimer's disease (AD) …
MRMD3. 0: A python tool and webserver for dimensionality reduction and data visualization via an ensemble strategy
Dimensionality reduction is a hot topic in machine learning that can help researchers find
key features from complex medical or biological data, which is crucial for biological …
key features from complex medical or biological data, which is crucial for biological …
The promise of convolutional neural networks for the early diagnosis of the Alzheimer's disease
P Erdogmus, AT Kabakus - Engineering Applications of Artificial …, 2023 - Elsevier
Alzheimer's Disease (AD) is one of the most devastating neurologic disorders, if not the
most, as there is no cure for this disease, and its symptoms eventually become severe …
most, as there is no cure for this disease, and its symptoms eventually become severe …
Multimodal fusion diagnosis of the Alzheimer's disease via lightweight CNN-LSTM model using magnetic resonance imaging (MRI)
EU Haq, Q Yong, Z Yuan, X Huarong… - … Signal Processing and …, 2025 - Elsevier
Alzheimer's disease is categorized as a primary neurodegenerative ailment that mostly
affects individuals in the elderly age and those reaching later stages of life. The recognition …
affects individuals in the elderly age and those reaching later stages of life. The recognition …
Single-objective and multi-objective mixed-variable grey wolf optimizer for joint feature selection and classifier parameter tuning
Feature selection plays an essential role in data preprocessing, which can extract valuable
information from extensive data, thereby enhancing the performance of machine learning …
information from extensive data, thereby enhancing the performance of machine learning …
Binary hiking optimization for gene selection: Insights from HNSCC RNA-Seq data
As a common challenge, high dimensionality in gene expression data leads to significant
computational difficulties in identifying disease markers. To address this issue, this study …
computational difficulties in identifying disease markers. To address this issue, this study …
[PDF][PDF] Handwriting Task-Selection based on the Analysis of Patterns in Classification Results on Alzheimer Dataset.
Alzheimer's Disease (AD) is a major disease associated with Dementia and a new case of
AD is discovered every three seconds. Research proved that handwriting can be used to …
AD is discovered every three seconds. Research proved that handwriting can be used to …
How word semantics and phonology affect handwriting of Alzheimer's patients: A machine learning based analysis
Using kinematic properties of handwriting to support the diagnosis of neurodegenerative
disease is a real challenge: non-invasive detection techniques combined with machine …
disease is a real challenge: non-invasive detection techniques combined with machine …
Automatic feature extraction with Vectorial Genetic Programming for Alzheimer's Disease prediction through handwriting analysis
Alzheimer's Disease (AD) is an incurable neurodegenerative disease that strongly impacts
the lives of the people affected. Even if, to date, there is no cure for this disease, its early …
the lives of the people affected. Even if, to date, there is no cure for this disease, its early …