Article

Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and Alzheimer’s disease

2020-02-11

Abstract excerpt

Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regression, support vector machines and Gaussian process models. With the advance of deep learning technology, the use of deep neural networks has also been proposed. In th...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6becea2c-b528-557b-9111-b389948336eb
DOI: 10.1101/2020.02.10.931824

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Normative modelling using deep autoencoders: a multi-cohort study on mild cognitive impairment and Alzheimer’s diseaseDOI 10.1101/2020.02.10.931824Read

A generalizable normative deep autoencoder for brain morphological anomaly detection: application to the multi-site StratiBip dataset on bipolar disorder in an external validation frameworkSemantic proximity Read

Quantitative Neuroimaging Meets Normative Modelling: The Last Mile for Precision Medicine ApplicationsSemantic proximity Read

Non-Gaussian Normative Modelling With Hierarchical Bayesian RegressionSemantic proximity Read

Judged by your neighbors: Brain structural normativity profiles for large and heterogeneous samplesSemantic proximity Read

Incorporating Multi-threshold Polygenic Risk in Hippocampal-based Normative Models Improves Cognitive Decline PredictionSemantic proximity Read

Deep neural networks learn general and clinically relevant representations of the ageing brainSemantic proximity Read

Examining real-world Alzheimer’s disease heterogeneity using neuroanatomical normative modellingSemantic proximity Read

Generalized Normative Modeling: A One-Step Hierarchical Kernel Framework for Multi-Site Brain Charts with Self-Correcting Z-ScoresSemantic proximity Read

Evaluating the Generalizability of EEG-Based AI Models in Alzheimer’s and Dementia DiagnosisSemantic proximity Read

Normative modeling of neuroimaging data using generalized additive models of location scale and shapeSemantic proximity Read

Revealing Individual Neuroanatomical Heterogeneity in Alzheimer’s DiseaseSemantic proximity Read