AIMC Topic: Alzheimer Disease

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Cortical surface registration using unsupervised learning.

NeuroImage Jul 20, 2020
Non-rigid cortical registration is an important and challenging task due to the geometric complexity of the human cortex and the high degree of inter-subject variability. A conventional solution is to use a spherical representation of surface propert...
Cerebral Cortex Unsupervised Machine Learning Alzheimer Disease Neuroimaging Adult Male Aging Deep Learning Cognitive Dysfunction Models, Theoretical Magnetic Resonance Imaging Female Aged Aged, 80 and over Young Adult Humans
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Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Aging Jul 9, 2020
Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathoge...
Humans Brain Female Longitudinal Studies Magnetic Resonance Imaging Cluster Analysis Unsupervised Machine Learning Aged Aged, 80 and over Male Disease Progression Image Interpretation, Computer-Assisted Atrophy Bayes Theorem Amyloid beta-Peptides Alzheimer Disease
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Adapting 'Sunshine,' A Socially Assistive Chat Robot for Older Adults with Cognitive Impairment: A Pilot Study.

Journal of gerontological social work Jul 7, 2020
Female Aged Male Pilot Projects Humans Research Design Cognitive Dysfunction Robotics Alzheimer Disease Activities of Daily Living
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Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders.

Scientific reports Jul 3, 2020
Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now available. However, to compile a comprehensive pi...
Computer Simulation Disease Progression Deep Learning User-Computer Interface Humans Databases, Factual Brain Models, Statistical Cohort Studies Bayes Theorem Polymorphism, Single Nucleotide Translational Research, Biomedical Longitudinal Studies Alzheimer Disease Parkinson Disease
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Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis.

Neuron Jun 29, 2020
A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neu...
Alzheimer Disease Gene Regulatory Networks Humans Mice Animals Neurons Aging Machine Learning Gene Expression Profiling Transcriptome
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A Combined Deep-Learning and Lattice Boltzmann Model for Segmentation of the Hippocampus in MRI.

Sensors (Basel, Switzerland) Jun 28, 2020
Segmentation of the hippocampus (HC) in magnetic resonance imaging (MRI) is an essential step for diagnosis and monitoring of several clinical situations such as Alzheimer's disease (AD), schizophrenia and epilepsy. Automatic segmentation of HC struc...
Hippocampus Magnetic Resonance Imaging Humans Epilepsy Deep Learning Schizophrenia Image Processing, Computer-Assisted Alzheimer Disease
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Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie Jun 16, 2020
Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3b (C3b) and Protein Kinase R-like Endoplasmic Reticulum Kinase (PERK), have been demonstrated to be involved in pathogenesis pathways for Alzheimer's ...
Molecular Targeted Therapy Quantitative Structure-Activity Relationship Nootropic Agents Molecular Structure Molecular Dynamics Simulation Alzheimer Disease Drug Discovery Humans Plant Extracts Animals Artificial Intelligence Cognition Molecular Docking Simulation Brain Signal Transduction Computer-Aided Design Drug Design
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Stratifying patients using fast multiple kernel learning framework: case studies of Alzheimer's disease and cancers.

BMC medical informatics and decision making Jun 16, 2020
BACKGROUND: Predictive patient stratification is greatly emerging, because it allows us to prospectively identify which patients will benefit from what interventions before their condition worsens. In the biomedical research, a number of stratificati...
Machine Learning Neoplasms Magnetic Resonance Imaging Alzheimer Disease Humans
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MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer's Disease: A Survey.

Sensors (Basel, Switzerland) Jun 7, 2020
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer's disease (...
Humans Neural Networks, Computer Brain Deep Learning Magnetic Resonance Imaging Alzheimer Disease
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Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on F-Florbetapir PET Using ADNI Data.

AJNR. American journal of neuroradiology Jun 4, 2020
BACKGROUND AND PURPOSE: Cortical amyloid quantification on PET by using the standardized uptake value ratio is valuable for research studies and clinical trials in Alzheimer disease. However, it is resource intensive, requiring co-registered MR imagi...
Plaque, Amyloid Ethylene Glycols Deep Learning Image Processing, Computer-Assisted Radiopharmaceuticals Brain Alzheimer Disease Female Aniline Compounds Humans Aged Positron-Emission Tomography Male Neuroimaging Fluorine Radioisotopes
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