Decoding cognitive health using machine learning: A comprehensive evaluation for diagnosis of significant memory concern
The timely identification of significant memory concern (SMC) is crucial for proactive
cognitive health management, especially in an aging population. Detecting SMC early …
cognitive health management, especially in an aging population. Detecting SMC early …
[PDF][PDF] Application of Machine Learning to the Process of Crop Selection Based on Land Dataset
Annotation: We are well recognised that the vast majority of Indians work in agriculture. Most
farmers always grow the same thing, always use the same amount of fertilizer, and always …
farmers always grow the same thing, always use the same amount of fertilizer, and always …
Classification of Satellite Photographs Utilizing the K-Nearest Neighbor Algorithm
SS Priscila, SS Rajest, R Regin… - … Asian Journal of …, 2023 - cajmtcs.centralasianstudies.org
Categorizing the various components of a satellite image is necessary for producing
thematic maps, which requires the image to be analysed and classified first. We have …
thematic maps, which requires the image to be analysed and classified first. We have …
Early detection of dementia using artificial intelligence and multimodal features with a focus on neuroimaging: A systematic literature review
O Grigas, R Maskeliunas, R Damaševičius - Health and Technology, 2024 - Springer
Purpose This paper is a systematic literature review of the use of artificial intelligence
techniques to detect early dementia. It focuses on multi-modal feature analysis in …
techniques to detect early dementia. It focuses on multi-modal feature analysis in …
[HTML][HTML] Principal Component Analysis for ATM Facial Recognition Security
Abstract The Automated Teller Machine, also known as an ATM, has become the most
common method by which individuals withdraw cash for their own use. The transactions that …
common method by which individuals withdraw cash for their own use. The transactions that …
A computational pipeline towards large-scale and multiscale modeling of traumatic axonal injury
Contemporary biomechanical modeling of traumatic brain injury (TBI) focuses on either the
global brain as an organ or a representative tiny section of a single axon. In addition, while it …
global brain as an organ or a representative tiny section of a single axon. In addition, while it …
Prior-Guided Adversarial Learning With Hypergraph for Predicting Abnormal Connections in Alzheimer's Disease
Alzheimer's disease (AD) is characterized by alterations of the brain's structural and
functional connectivity during its progressive degenerative processes. Existing auxiliary …
functional connectivity during its progressive degenerative processes. Existing auxiliary …
[PDF][PDF] OTP As a Service in the Cloud Allows for Authentication of Multiple Services
Annotation: Users no longer trust traditional password-based authentication methods since
so many online services now interact with one another. Credentials obtained online are …
so many online services now interact with one another. Credentials obtained online are …
[HTML][HTML] Investigating Deep Learning for Early Detection and Decision-Making in Alzheimer's Disease: A Comprehensive Review
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people
worldwide, making early detection essential for effective intervention. This review paper …
worldwide, making early detection essential for effective intervention. This review paper …
Using principal component analysis to determine which vestibular stimuli provide best biomarkers for separating Alzheimer's from mixed Alzheimer's disease
Alzheimer's disease (AD) is often mixed with cerebrovascular disease (AD-CVD).
Heterogeneity of dementia etiology and the overlapping of neuropathological features of AD …
Heterogeneity of dementia etiology and the overlapping of neuropathological features of AD …