AIMC Topic: Alzheimer Disease
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A confounder controlled machine learning approach: Group analysis and classification of schizophrenia and Alzheimer's disease using resting-state functional network connectivity.
PloS one
May 20, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) has increasingly been used to study both Alzheimer's disease (AD) and schizophrenia (SZ). While most rs-fMRI studies being conducted in AD and SZ compare patients to healthy controls, it i...
Alzheimer's disease early screening and staged detection with plasma proteome using machine learning and convolutional neural network.
The European journal of neuroscience
May 19, 2024
Alzheimer's disease (AD) stands as the prevalent progressive neurodegenerative disease, precipitating cognitive impairment and even memory loss. Amyloid biomarkers have been extensively used in the diagnosis of AD. However, amyloid proteins offer lim...
A ResNet mini architecture for brain age prediction.
Scientific reports
May 16, 2024
The brain presents age-related structural and functional changes in the human life, with different extends between subjects and groups. Brain age prediction can be used to evaluate the development and aging of human brain, as well as providing valuab...
CKG-IMC: An inductive matrix completion method enhanced by CKG and GNN for Alzheimer's disease compound-protein interactions prediction.
Computers in biology and medicine
May 14, 2024
Alzheimer's disease (AD) is one of the most prevalent chronic neurodegenerative disorders globally, with a rapidly growing population of AD patients and currently no effective therapeutic interventions available. Consequently, the development of ther...
Robot-based solution for helping Alzheimer patients.
SLAS technology
May 8, 2024
Alzheimer's is a progressive and debilitating neurological disorder characterized by cognitive decline, memory loss, and impaired daily functioning. It is an irreversible brain disease that destroys memory, thinking, and the ability to carry out dail...
Comparative assessment of established and deep learning-based segmentation methods for hippocampal volume estimation in brain magnetic resonance imaging analysis.
NMR in biomedicine
May 7, 2024
In this study, our objective was to assess the performance of two deep learning-based hippocampal segmentation methods, SynthSeg and TigerBx, which are readily available to the public. We contrasted their performance with that of two established tech...
Deep Learning-Based Eye-Tracking Analysis for Diagnosis of Alzheimer's Disease Using 3D Comprehensive Visual Stimuli.
IEEE journal of biomedical and health informatics
May 6, 2024
Alzheimer's Disease (AD) is a neurodegenerative disorder that causes a continuous decline in cognitive functions and eventually results in death. An early AD diagnosis is important for taking active measures to slow its deterioration. Traditional dia...
Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.
Investigative radiology
Apr 23, 2024
OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. T...
PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies.
Genome medicine
Apr 16, 2024
Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interpre...
A machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases.
Clinica chimica acta; international journal of clinical chemistry
Apr 15, 2024
BACKGROUND AND AIMS: A machine learning algorithm based on circulating metabolic biomarkers for the predictions of neurological diseases (NLDs) is lacking. To develop a machine learning algorithm to compare the performance of a metabolic biomarker-ba...
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