A 2026 ADNI/A4 validation study found that Alzheimer’s plasma-biomarker machine-learning models still ranked amyloid PET status well across cohorts, but the practical rule-out number moved hard: negative predictive value fell from 0.831 inside ADNI to 0.644 when the ADNI-trained model was applied to A4.1 Research Highlights 1,707-person ADNI/A4 test: researchers trained amyloid PET prediction models …
A 2026 TADPOLE modeling study reported that a sequential neural process with normalizing flows predicted future Alzheimer diagnostic stage with mAUC 0.965 ± 0.006, ahead of the authors’ earlier sequential-neural-process model at 0.937 ± 0.014.1 The result is a strong benchmark signal for uncertainty-aware disease-progression AI, but it is still retrospective modeling evidence rather than …
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 machine-learning analysis of 110 adults with generalized anxiety disorder predicted 2-week digital mindfulness engagement with R2 = 82.1% in a top-10 predictor model, and the model favored mindfulness prompts over self-monitoring prompts for engagement (d = 1.447, p < .001).1 The calibrated read is that engagement with brief app-based mindfulness may be matchable, …
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 serum multiomics study linked occupational noise exposure to tinnitus severity mostly through metabolism: 10 metabolites, including GABA, fumaric acid, and steroid hormone precursors, statistically mediated 92% of the exposure-tinnitus association.1 The result is not a clinical blood test yet, but it pushes tinnitus biology beyond the ear-only frame toward a metabolism-immunity model that …
A 2026 Scientific Reports study of Maryland suicide-death records found that an XGBoost machine-learning model could reach 96.1% positive predictive value in hospital-discharge data at the top 0.1% risk threshold, but it still detected only 46.7% of suicide deaths in that cohort. Research Highlights Precision improved at the narrowest threshold: XGBoost reached PPV 0.961 in …