Article

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

2026-05-23

Abstract excerpt

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimer’s disease and related dementias (ADRDs). As many individuals with ADRDs have mixed pathologies (β-amyloid, pathologic tau, cerebrovascular disease, vascular brain injury, pathologic TDP-43, hippocampal sclerosis, Lewy bodies), there is interest in determining how accurately we can infer these pathologic cha...

Topics

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

Identifiers and source

Literature Corpus work: 6f4ff291-b202-555a-b03d-76e024cd947b
DOI: 10.64898/2026.05.20.726332

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine LearningDOI 10.64898/2026.05.20.726332Read

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

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

Comprehensive evaluation of AT(N) imaging biomarkers for predicting cognitionSemantic proximity Read

Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future.Semantic proximity Read

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

Structural heterogeneity reveals distinct amyloidopathies in Alzheimer’s diseaseSemantic proximity Read

Soluble Amyloid-Beta Isoforms Predict Downstream Alzheimer’s Disease PathologySemantic proximity Read

Elucidating the neuropathological and molecular heterogeneity of amyloid-beta and tau in Alzheimer's disease through machine learning and transcriptomic integrationSemantic proximity Read

Deep learning-driven risk-based subtyping of cognitively impaired individualsSemantic proximity Read

MRI-Based Multi-Class Relevance Vector Machine Classification of Neurodegenerative DiseasesSemantic proximity Read

A large-scale multi-centre study characterising atrophy heterogeneity in Alzheimer’s diseaseSemantic proximity Read