ArticleAlzheimer's & dementia (Amsterdam, Netherlands)2021
Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression.
Article in Alzheimer's & dementia (Amsterdam, Netherlands), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Article
- A review of AI-based radiogenomics in neurodegenerative disease.Frontiers in big data · 2025Review
- The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Review
- Vertical Graphene-Based Printed Electrochemical Biosensor for Simultaneous Detection of Four Alzheimer's Disease Blood Biomarkers.Biosensors · 2023Article
- Portable Vertical Graphene@Au-Based Electrochemical Aptasensing Platform for Point-of-Care Testing of Tau Protein in the Blood.Biosensors · 2022Article
- Exploiting deep transfer learning for the prediction of functional non-coding variants using genomic sequence.Bioinformatics (Oxford, England) · 2022Article
- Article
- Portable electrochemical micro-workstation platform for simultaneous detection of multiple Alzheimer's disease biomarkers.Mikrochimica acta · 2022Article
- Transfer Learning Approaches for Neuroimaging Analysis: A Scoping Review.Frontiers in artificial intelligence · 2022Article
- Multi-task deep autoencoder to predict Alzheimer's disease progression using temporal DNA methylation data in peripheral blood.Computational and structural biotechnology journal · 2022Article
- Research on Pathogenic Hippocampal Voxel Detection in Alzheimer's Disease Using Clustering Genetic Random Forest.Frontiers in psychiatry · 2022Article
- Electrochemical immunosensor based on superwettable microdroplet array for detecting multiple Alzheimer's disease biomarkers.Frontiers in bioengineering and biotechnology · 2022Article
- Prediction of Early Alzheimer Disease by Hippocampal Volume Changes under Machine Learning Algorithm.Computational and mathematical methods in medicine · 2022Article
- Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression.Alzheimer's & dementia (Amsterdam, Netherlands) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
introductionGenome-wide association studies (GWAS) for late onset Alzheimer's disease (AD) may miss genetic variants relevant for delineating disease stages when using clinically defined case/control as a phenotype due to its loose definition and heterogeneity.
methodsWe use a transfer learning technique to train three-dimensional convolutional neural network (CNN) models based on structural magnetic resonance imaging (MRI) from the screening stage in the Alzheimer's Disease Neuroimaging Initiative consortium to derive image features that reflect AD progression.
resultsCNN-derived image phenotypes are significantly associated with fasting metabolites related to early lipid metabolic changes as well as insulin resistance and with genetic variants mapped to candidate genes enriched for amyloid beta degradation, tau phosphorylation, calcium ion binding-dependent synaptic loss, DISCUSSION: This is the first attempt to show that non-invasive MRI biomarkers are linked to AD progression characteristics, reinforcing their use in early AD diagnosis and monitoring.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.