A 2026 medRxiv preprint found that REDDI, a resting-state magnetoencephalography machine-learning pipeline, separated mild cognitive impairment, multiple sclerosis, Parkinson’s disease, and amyotrophic lateral sclerosis with 0.81 ± 0.04 balanced accuracy across 5 folds.1 That is a meaningful jump over the prior 67.1% MEG benchmark, but it is still research-stage decision support rather than a clinical …
A 2026 ADNI study reported 85.23% accuracy for ANA-GNN, a graph neural network that combined structural MRI regional features with clinical variables to classify cognitively normal controls, mild cognitive impairment, and Alzheimer’s disease.1 The result is useful, but the clinical-feature ablation dropped accuracy to 68.35%, so the model should be read as multimodal decision-support research, …
A 2026 Molecular Psychiatry study found that RVI-AD, a structural-MRI score measuring how closely a person’s brain anatomy matches an Alzheimer’s disease pattern, predicted mild-cognitive-impairment conversion to dementia most strongly over the next 3 years: OR 2.16, 95% CI 1.81-2.57, p < 2e-16, AUC 0.70.1 Research Highlights Short-term conversion signal: in 965 ADNI participants with …
Until recently, Alzheimer’s pathology could only be confirmed in living patients via PET imaging or lumbar puncture. Plasma p-tau217 changed that calculus — but how to interpret a positive result depends substantially on APOE genotype.1 Research Highlights Plasma p-tau217 is a blood biomarker that rises years before Alzheimer’s symptoms. The 2024 Alzheimer’s Association revised criteria …