Papers Alzheimer's Detection
“Alzheimer's Detection” 태그가 달린 논문 14편 · 필터 해제
Single Domain Generalization for Alzheimer's Detection from 3D MRIs with Pseudo-Morphological Augmentations and Contrastive Learning
Although Alzheimer's disease detection via MRIs has advanced significantly thanks to contemporary deep learning models, challenges such as class imbalance, protocol variations, and limited dataset diversity often hinder …
Alzheimer's DetectionAlzheimer's Disease DetectionContrastive LearningDiversity+1Unlocking Neural Transparency: Jacobian Maps for Explainable AI in Alzheimer's Detection
Alzheimer's disease (AD) leads to progressive cognitive decline, making early detection crucial for effective intervention. While deep learning models have shown high accuracy in AD diagnosis, their lack of interpretabil…
Alzheimer's DetectionDiagnosticADAM-1: AI and Bioinformatics for Alzheimer's Detection and Microbiome-Clinical Data Integrations
The Alzheimer's Disease Analysis Model Generation 1 (ADAM) is a multi-agent large language model (LLM) framework designed to integrate and analyze multi-modal data, including microbiome profiles, clinical datasets, and e…
Alzheimer's DetectionBinary ClassificationLanguage ModelingLanguage Modelling+4Hybrid Transformer for Early Alzheimer's Detection: Integration of Handwriting-Based 2D Images and 1D Signal Features
Alzheimer's Disease (AD) is a prevalent neurodegenerative condition where early detection is vital. Handwriting, often affected early in AD, offers a non-invasive and cost-effective way to capture subtle motor changes. S…
Alzheimer's DetectionNeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes
Although modern imaging technologies allow us to study connectivity between two distinct brain regions in-vivo, an in-depth understanding of how anatomical structure supports brain function and how spontaneous functional…
2-task Classification4-task ClassificationAlzheimer's DetectionFunctional Connectivity+4AD-Lite Net: A Lightweight and Concatenated CNN Model for Alzheimer's Detection from MRI Images
Alzheimer's Disease (AD) is a non-curable progressive neurodegenerative disorder that affects the human brain, leading to a decline in memory, cognitive abilities, and eventually, the ability to carry out daily tasks. Ma…
Alzheimer's DetectionLeveraging Bi-Focal Perspectives and Granular Feature Integration for Accurate Reliable Early Alzheimer's Detection
Being the most commonly known neurodegeneration, Alzheimer's Disease (AD) is annually diagnosed in millions of patients. The present medical scenario still finds the exact diagnosis and classification of AD through neuro…
Alzheimer's DetectionAlzheimer's Magnetic Resonance Imaging Classification Using Deep and Meta-Learning Models
Deep learning, a cutting-edge machine learning approach, outperforms traditional machine learning in identifying intricate structures in complex high-dimensional data, particularly in the domain of healthcare. This study…
Alzheimer's DetectionMeta-LearningLongitudinal Volumetric Study for the Progression of Alzheimer's Disease from Structural MRI
Alzheimer's Disease (AD) is an irreversible neurodegenerative disorder affecting millions of individuals today. The prognosis of the disease solely depends on treating symptoms as they arise and proper caregiving, as the…
Alzheimer's DetectionImage RegistrationPrognosisSkull StrippingAlzheimer's Disease Detection from Spontaneous Speech and Text: A review
In the past decade, there has been a surge in research examining the use of voice and speech analysis as a means of detecting neurodegenerative diseases such as Alzheimer's. Many studies have shown that certain acoustic …
Alzheimer's DetectionAlzheimer's Disease DetectionArticlesFeature EngineeringCross-Lingual Transfer Learning for Alzheimer's Detection From Spontaneous Speech
Alzheimer's disease (AD) is a progressive neurodegenerative disease most often associated with memory deficits and cognitive decline. With the aging population, there has been much interest in automated methods for cogni…
Alzheimer's DetectionCross-Lingual TransferTransfer LearningTransfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Disease
Early diagnosis of Alzheimer's disease (AD) is essential in preventing the disease's progression. Therefore, detecting AD from neuroimaging data such as structural magnetic resonance imaging (sMRI) has been a topic of in…
Alzheimer's Detectionimage-classificationImage ClassificationMedical Image Classification+1Deep Multi-Branch CNN Architecture for Early Alzheimer's Detection from Brain MRIs
Alzheimer's disease (AD) is a neuro-degenerative disease that can cause dementia and result severe reduction in brain function inhibiting simple tasks especially if no preventative care is taken. Over 1 in 9 Americans su…
Alzheimer's DetectionAlzheimer's Disease DetectionContrastive Learning with Continuous Proxy Meta-Data for 3D MRI Classification
Traditional supervised learning with deep neural networks requires a tremendous amount of labelled data to converge to a good solution. For 3D medical images, it is often impractical to build a large homogeneous annotate…
Alzheimer's DetectionContrastive LearningMRI classification