AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Alzheimer Disease

Showing 231 to 240 of 895 articles

Clear Filters

Bayesian Tensor Modeling for Image-based Classification of Alzheimer's Disease.

Neuroinformatics
Tensor-based representations are being increasingly used to represent complex data types such as imaging data, due to their appealing properties such as dimension reduction and the preservation of spatial information. Recently, there is a growing lit...

CLADSI: Deep Continual Learning for Alzheimer's Disease Stage Identification Using Accelerometer Data.

IEEE journal of biomedical and health informatics
Alzheimer's disease (AD) is a neurodegenerative disorder that can cause a significant impairment in physical and cognitive functions. Gait disturbances are also reported as a symptom of AD. Previous works have used Convolutional Neural Networks (CNNs...

Integrating AI in fighting advancing Alzheimer: diagnosis, prevention, treatment, monitoring, mechanisms, and clinical trials.

Current opinion in structural biology
The application of artificial intelligence (AI) in neurology is a growing field offering opportunities to improve accuracy of diagnosis and treatment of complicated neuronal disorders, plus fostering a deeper understanding of the aetiologies of these...

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement.

Genome medicine
BACKGROUND: Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic da...

Exploring Brain Effective Connectivity Networks Through Spatiotemporal Graph Convolutional Models.

IEEE transactions on neural networks and learning systems
Learning brain effective connectivity networks (ECN) from functional magnetic resonance imaging (fMRI) data has gained much attention in recent years. With the successful applications of deep learning in numerous fields, several brain ECN learning me...

A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting.

IEEE transactions on neural networks and learning systems
The detection and segmentation of stained cells and nuclei are essential prerequisites for subsequent quantitative research for many diseases. Recently, deep learning has shown strong performance in many computer vision problems, including solutions ...

Hypergraph Structural Information Aggregation Generative Adversarial Networks for Diagnosis and Pathogenetic Factors Identification of Alzheimer's Disease With Imaging Genetic Data.

IEEE transactions on neural networks and learning systems
Alzheimer's disease (AD) is a neurodegenerative disease with profound pathogenetic causes. Imaging genetic data analysis can provide comprehensive insights into its causes. To fully utilize the multi-level information in the data, this article propos...

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annual...

Alzheimer's disease diagnosis from multi-modal data via feature inductive learning and dual multilevel graph neural network.

Medical image analysis
Multi-modal data can provide complementary information of Alzheimer's disease (AD) and its development from different perspectives. Such information is closely related to the diagnosis, prevention, and treatment of AD, and hence it is necessary and c...