Article

MRI-Based Multi-Class Relevance Vector Machine Classification of Neurodegenerative Diseases

2024-10-08

Abstract excerpt

Machine learning algorithms are a promising automated candidate that can help mitigate the growing need for dementia experts. Despite the substantial development in MRI-based machine learning analyses, case misclassification is a universal finding, yet the reasons behind misclassification are poorly understood. We implemented a multi-class classification approach that uses relevance vector machine and logistic cla...

Topics

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

Identifiers and source

Literature Corpus work: dd9b6297-91f8-5686-b9c8-3397cef0e80b
DOI: 10.1101/2024.10.07.24315054

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

MRI-Based Multi-Class Relevance Vector Machine Classification of Neurodegenerative DiseasesDOI 10.1101/2024.10.07.24315054Read

Comparative Analysis of Machine Learning Algorithms for Multi-Syndrome Classification of Neurodegenerative SyndromesSemantic proximity Read

Prediction, prognosis and monitoring of neurodegeneration at biobank-scale via machine learning and imagingSemantic proximity Read

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine LearningSemantic proximity Read

Diagnosis and Prognosis Using Machine Learning Trained on Brain Morphometry and White Matter ConnectomesSemantic proximity Read

Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic DataSemantic proximity Read

A Practical Alzheimer Disease Classifier via Brain Imaging-Based Deep Learning on 85,721 SamplesSemantic proximity Read

Machine Learning methods for predicting conversion from mild cognitive impairment to Alzheimer’s disease. A systematic review.Semantic proximity Read

Risk Score Stratification of Alzheimer’s Disease and Mild Cognitive Impairment using Deep LearningSemantic proximity Read

Integrating Machine Learning Pipelines for Multimodal Biomarker Prediction in Alzheimer’s and Parkinson’s Disease: A Component of the Neurodiagnoses FrameworkSemantic proximity Read

Single-subject classification of presymptomatic frontotemporal dementia mutation carriers using multimodal MRI.Semantic proximity Read

A Practical Alzheimer Disease Classifier via Brain Imaging-Based Deep Learning on 85,721 SamplesSemantic proximity Read

Prediction of clinical and biomarker conformed Alzheimer’s disease and mild cognitive impairment from multi-feature brain structural MRISemantic proximity Read